sql for data scientists renee m p teate

Jump-start your career as a data scientist—learn to develop datasets for exploration, analysis, and machine learning SQL for Data Scientists: A Beginner's Guide for Building Datasets for Analysis is a resource that’s dedicated to the Structured Query Language (SQL) and dataset design skills that data scientists use most. Aspiring data scientists will learn how to how to construct datasets for exploration, analysis, and machine learning. You can also discover how to approach query design and develop SQL code to extract data insights while avoiding common pitfalls. You may be one of many people who are entering the field of Data Science from a range of professions and educational backgrounds, such as business analytics, social science, physics, economics, and computer science. Like many of them, you may have conducted analyses using spreadsheets as data sources, but never retrieved and engineered datasets from a relational database using SQL, which is a programming language designed for managing databases and extracting data. This guide for data scientists differs from other instructional guides on the subject. It doesn’t cover SQL broadly. Instead, you’ll learn the subset of SQL skills that data analysts and data scientists use frequently. You’ll also gain practical advice and direction on ... Unknown localization key: "more"

Objev podobné jako SQL for Data Scientists - Renee M. P. Teate

Statistical methods are a key part of data science, yet few data scientists have formal statistical training. Courses and books on basic statistics rarely cover the topic from a data science perspective. The second edition of this popular guide adds comprehensive examples in Python, provides practical guidance on applying statistical methods to data science, tells you how to avoid their misuse, and gives you advice on what's important and what's not.Many data science resources incorporate statistical methods but lack a deeper statistical perspective. If you're familiar with the R or Python programming languages and have some exposure to statistics, this quick reference bridges the gap in an accessible, readable format.With this book, you'll learn:Why exploratory data analysis is a key preliminary step in data scienceHow random sampling can reduce bias and yield a higher-quality dataset, even with big dataHow the principles of experimental design yield definitive answers to questionsHow to use regression to estimate outcomes and detect anomaliesKey classification techniques for predicting which categories a record belongs toStatistical machine learning methods that "learn" from dataUnsupervised learning methods for extracting meaning from unlabeled data

Objev podobné jako Practical Statistics for Data Scientists - Peter Bruce, Andrew Bruce, Peter Gedeck

This practical book bridges the gap between data science and software engineering, clearly explaining how to apply the best practices from software engineering to data science.

Objev podobné jako Software Engineering for Data Scientists - Catherine Nelson

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SQL for Smarties was hailed as the first book devoted explicitly to the advanced techniques needed to transform an experienced SQL programmer into an expert. Now, 20 years later and in its fifth edition, this classic reference still reigns supreme as the only book written by a SQL master that teaches programmers and practitioners to become SQL masters themselves! These are not just tips and techniques; also offered are the best solutions to old and new challenges. Joe Celko conveys the way you need to think in order to get the most out of SQL programming efforts for both correctness and performance.New to the fifth edition, Joe features new examples to reflect the ANSI/ISO Standards so anyone can use it. He also updates data element names to meet new ISO-11179 rules with the same experience-based teaching style that made the previous editions the classics they are today. You will learn new ways to write common queries, such as finding coverings, partitions, runs in data, auctions and inventory, relational divisions and so forth.SQL for Smarties explains some of the principles of SQL programming as well as the code. A new chapter discusses design flaws in DDL, such as attribute splitting, non-normal ... Unknown localization key: "more"

Objev podobné jako Joe Celko's SQL for Smarties - Joe Celko

Get ready to make SQL easy! Updated for the latest version of SQL, the new edition of this perennial bestseller shows programmers and web developers how to use SQL to build relational databases and get valuable information from them. Covering everything you need to know to make working with SQL easier than ever, topics include how to use SQL to structure a DBMS and implement a database design; secure a database; and retrieve information from a database; and much more.  SQL is the international standard database language used to create, access, manipulate, maintain, and store information in relational database management systems (DBMS) such as Access, Oracle, SQL Server, and MySQL. SQL adds powerful data manipulation and retrieval capabilities to conventional languages—and this book shows you how to harness the core element of relational databases with ease. Server platform that gives you choices of development languages, data types, on-premises or cloud, and operating systemsFind great examples on the use of temporal dataJump right in—without previous knowledge of database programming or SQL As database-driven websites continue to grow in popularity—and complexity—SQL For Dummies is the easy-to-understand, go-to resource you need to use it seamlessly.

Objev podobné jako SQL For Dummies - Allen G. Taylor

Query and modify data effectively with the latest T-SQL features Master Transact-SQL''s fundamentals, and write correct, robust code for querying and modifying data with modern Microsoft data technologies, including SQL Server 2022, Azure SQL Database, and Azure SQL Managed Instance. Long-time Microsoft Data Platform MVP Itzik Ben-Gan explains key T-SQL concepts, helping you apply your knowledge with hands-on exercises. Ben-Gan first introduces T-SQL''s theory and underlying logic, illuminating it as both a language and a way of thinking. Next, he walks through core topics, including logical query processing, single table queries, joins, subqueries, table expressions, set operators, data analysis, data modifications, temporal tables, and transactions and concurrency. Building on this foundation, you''ll enhance your coding capabilities, from programmatic constructs to the powerful new SQL Graph. Throughout, Ben-Gan presents reusable T-SQL sample code that works in cloud, on-premises, and hybrid environments. Microsoft Data Platform MVP Itzik Ben-Gan helps you: Understand why T-SQL works as it does, so you can write better code Review relational theory elements and modern SQL Server architecture Create tables and defi ne data integrity Build single-table SELECT queries, multiple-table joins, and subqueries Utilize derived tables, Common Table Expressions, views, inline table-valued functions, and APPLY Make the most ... Unknown localization key: "more"

Objev podobné jako T-SQL Fundamentals - Ben-Gan Itzik

Conquer SQL Server 2022 and Azure SQL administration from the inside out! Dive into SQL Server 2022 administration and grow your Microsoft SQL Server data platform skillset. This well-organized reference packs in timesaving solutions, tips, and workarounds, all you need to plan, implement, deploy, provision, manage, and secure SQL Server 2022 in any environment: on-premises, cloud, or hybrid, including detailed, dedicated chapters on Azure SQL Database and Azure SQL Managed Instance. Nine experts thoroughly tour DBA capabilities available in the SQL Server 2022 Database Engine, SQL Server Data Tools, SQL Server Management Studio, PowerShell, and much more. You''ll find extensive new coverage of Azure SQL Database and Azure SQL Managed Instance, both as a cloud platform of SQL Server and in their new integrations with SQL Server 2022, information available in no other book. Discover how experts tackle today''s essential tasks and challenge yourself to new levels of mastery. Identify low-hanging fruit and practical, easy wins for improving SQL Server administration Get started with modern SQL Server tools, including SQL Server Management Studio, and Azure Data Studio Upgrade your SQL Server administration skillset to new features of SQL Server 2022, Azure SQL Database, Azure SQL Managed Instance, and SQL Server ... Unknown localization key: "more"

Objev podobné jako SQL Server 2022 Administration Inside Out - Elizabeth Noble, William Assaf, Randolph West, Meagan Longoria, Martina D'Antoni, Louis Davidson

Using PL/SQL for Oracle Database 21c, you can build solutions that deliver unprecedented performance and efficiency in any environment, including the cloud. Oracle PL/SQL by Example, Sixth Edition, teaches all the PL/SQL skills you''ll need, through real-world labs and extensive examples. Now fully updated for the newest version of PL/SQL 21c, it covers everything from basic syntax and program control through the latest optimization and tuning enhancements. Step by step, you''ll walk through every key task, mastering today''s most valuable Oracle 21c PL/SQL programming techniques on your own. Start by downloading the supporting schema and exercises from informit.com/title/9780138062835. Once you''ve done an exercise, the author doesn''t just present the answer: She offers an in-depth discussion introducing deeper insights and modern best practices. This book''s approach fully reflects the author''s award-winning experience teaching PL/SQL to professionals at Columbia University in New York City. New database developers and DBAs can use it to get productive fast; experienced PL/SQL programmers will find it to be a superb Oracle Database 21c solutions reference. New in This Edition Updated code examples throughout New iteration controls for the FOR LOOP statement, such as stepped range, multiple iterations, collection, and cursor iterations Enhancements for PL/SQL qualified expressions ... Unknown localization key: "more"

Objev podobné jako Oracle PL/SQL by Example - Benjamin Rosenzweig, Elena Rakhimov

Use SQL to get the data you need in no time at all! Learn to read and write basic queries, troubleshoot common problems, and control your own business data in just 24 short lessons–no programming experience required! In Learn SQL in a Month of Lunches you''ll master useful SQL skills like: Write your own SQL queries See only the data you need in large datasets Easily filter, sort, and cluster data Master basic data manipulation techniques Safely create, update, and delete data Structured Query Language (SQL) is the standard way to get specific datasets out of large relational databases. If you use Excel, Tableau, or PowerBI to crunch business data, you''ve probably seen a lot of SQL already. And guess what? It''s easy to master the most useful parts of SQL! In just a few quick lessons, you can learn to write your own queries, modify existing SQL statements, and add a new superpower to your bag of tricks. Learn SQL in a Month of Lunches introduces you to the most useful parts of SQL for business data analysis. This practical book gives you instantly-useful techniques starting from the first short chapter. 25-year SQL veteran Jeff Iannucci makes SQL a ... Unknown localization key: "more"

Objev podobné jako Learn SQL in a Month of Lunches - Jeff Iannucci

Use window functions to write simpler, better, more efficient T-SQL queries Most T-SQL developers recognize the value of window functions for data analysis calculations. But they can do far more, and recent optimizations make them even more powerful. In T-SQL Window Functions, renowned T-SQL expert Itzik Ben-Gan introduces breakthrough techniques for using them to handle many common T-SQL querying tasks with unprecedented elegance and power. Using extensive code examples, he guides you through window aggregate, ranking, distribution, offset, and ordered set functions. You’ll find a detailed section on optimization, plus an extensive collection of business solutions — including novel techniques available in no other book. Microsoft MVP Itzik Ben-Gan shows how to: • Use window functions to improve queries you previously built with predicates • Master essential SQL windowing concepts, and efficiently design window functions • Effectively utilize partitioning, ordering, and framing • Gain practical in-depth insight into window aggregate, ranking, offset, and statistical functions • Understand how the SQL standard supports ordered set functions, and find working solutions for functions not yet available in the language • Preview advanced Row Pattern Recognition (RPR) data analysis techniques • Optimize window functions in SQL Server and Azure SQL Database, making the ... Unknown localization key: "more"

Objev podobné jako T-SQL Window Functions - Ben-Gan Itzik

Learn the most important SQL skills and apply them in your job—quickly and efficiently! SQL (Structured Query Language) is the modern language that almost every relational database system supports for adding data, retrieving data, and modifying data in a database. Although basic visual tools are available to help end-users input common commands, data scientists, business intelligence analysts, Cloud engineers, Machine Learning programmers, and other professionals routinely need to query a database using SQL. Job Ready SQL provides you with the foundational skills necessary to work with data of any kind. Offering a straightforward ‘learn-by-doing’ approach, this concise and highly practical guide teaches you all the basics of SQL so you can apply your knowledge in real-world environments immediately. Throughout the book, each lesson includes clear explanations of key concepts and hands-on exercises that mirror real-world SQL tasks. Teaches the basics of SQL database creation and management using easy-to-understand languageHelps readers develop an understanding of fundamental concepts and more advanced applications such as data engineering and data scienceDiscusses the key types of SQL commands, including Data Definition Language (DDL) commands and Data Manipulation Language (DML) commandsIncludes useful reference information on querying SQL-based databasesJob Ready SQL is a must-have resource for students ... Unknown localization key: "more"

Objev podobné jako Job Ready SQL - Haythem ) Balti, Kimberly A. ) Weiss

Create a semantic model and analyse data using the tabular model in SQL Server 2016 Analysis Services to create corporate-level business intelligence (BI) solutions. Led by two BI experts, you will learn how to build, deploy, and query a tabular model by following detailed examples and best practices. This hands-on book shows you how to use the tabular model’s in-memory database to perform rapid analytics—whether you are new to Analysis Services or already familiar with its multidimensional model. Discover how to: Determine when a tabular or multidimensional model is right for your project Build a tabular model using SQL Server Data Tools in Microsoft Visual Studio 2015 Integrate data from multiple sources into a single, coherent view of company information Choose a data-modeling technique that meets your organisation’s performance and usability requirements Implement security by establishing administrative and data user roles Define and implement partitioning strategies to reduce processing time Use Tabular Model Scripting Language (TMSL) to execute and automate administrative tasks Optimise your data model to reduce the memory footprint for VertiPaq Choose between in-memory (VertiPaq) and pass-through (DirectQuery) engines for tabular models Select the proper hardware and virtualisation configurations Deploy and manipulate tabular models from C# and PowerShell ... Unknown localization key: "more"

Objev podobné jako Tabular Modeling in Microsoft SQL Server Analysis Services - Marco Russo, Alberto Ferrari

For more than thirty years, Writing for Social Scientists has been a lifeboat for writers in all fields, from beginning students to published authors. It starts with a powerful reassurance: Academic writing is stressful, and even accomplished scholars like sociologist Howard S. Becker struggle with it. And it provides a clear solution: In order to learn how to write, take a deep breath and then begin writing. Revise. Repeat. This is not a book about sociological writing. Instead, Becker applies his sociologist's eye to some of the common problems all academic writers face, including trying to get it right the first time, failing, and therefore not writing at all; getting caught up in the trappings of "proper" academic writing; writing to impress rather than communicate with readers; and struggling with the when and how of citations. He then offers concrete advice, based on his own experiences and those of his students and colleagues, for overcoming these obstacles and gaining confidence as a writer. While the underlying challenges of writing have remained the same since the book first appeared, the context in which academic writers work has changed dramatically, thanks to rapid changes in technology and ever greater institutional pressures. This ... Unknown localization key: "more"

Objev podobné jako Writing for Social Scientists, Third Edition - Howard S. Becker

From top experts in the world of science comes this definitive and clear guide to biology, published in partnership with the Royal Society of Biology.In Your Expert Guide: Biology for Young Scientists, discover the foundations of this crucial and exciting branch of science. Learn to think like a biologist, understand what makes up a living thing and explore the biological building blocks of everything around you - from the first organisms on Earth to the slime moulds in the forest, from the lab to the South Pole. Get an expert view of how biology underpins our understanding of life!Published in partnership with The Royal Society of Biology, a renowned organisation dedicated to a world that values biology''s contribution to improving life for all. With approachable artwork by Ola Szpunar, curious readers age 8+ can see biology come alive.Books in the Your Expert Guide series:With Royal Society of Chemistry: The Periodic Table / Chemistry for Young ScientistsWith Royal Society of Biology: The Human Body / Biology for Young ScientistsWith Institute of Physics: The Universe / Physics for Young Scientists

Objev podobné jako Your Expert Guide: Biology for Young Scientists - Tom Jackson, Helen Watson

America''s Test Kitchen Kids brings delicious science to your kitchen! Over 75 kid-tested, kid-approved recipes and experiments teach young chefs about the fun and fascinating science of food. This is the fourth book in the New York Times bestselling cookbook series for Young Chefs.Why do some cheeses melt better than others? Why does popcorn "pop"? How does gelatin work? Answer these questions (and wow your friends and family!) by cooking the best-ever skillet pizza, easy chocolate popcorn, and galactic mirror cake... and more! Plus, fun science experiments to do in your home kitchen. With The Complete Cookbook for Young Scientists, emerging scientists and young chefs will feel confident in the kitchen, proud of their accomplishments, and learn the basics of food science along the way.

Objev podobné jako The Complete Cookbook for Young Scientists - America's Test Kitchen Kids

This practical book shows data analysts, data engineers, BI developers, and data scientists how to create a true self-service transformation platform through the use of dynamic SQL.

Objev podobné jako Analytics Engineering with SQL and Dbt - Helder Russa, Rui Machado

This textbook introduces readers to the theoretical aspects of machine learning (ML) algorithms, starting from simple neuron basics, through complex neural networks, including generative adversarial neural networks and graph convolution networks. Most importantly, this book helps readers to understand the concepts of ML algorithms and enables them to develop the skills necessary to choose an apt ML algorithm for a problem they wish to solve. In addition, this book includes numerous case studies, ranging from simple time-series forecasting to object recognition and recommender systems using massive databases. Lastly, this book also provides practical implementation examples and assignments for the readers to practice and improve their programming capabilities for the ML applications.

Objev podobné jako Machine Learning for Computer Scientists and Data Analysts - Houman Homayoun, Zhiqian Chen, Setareh Rafatirad, Sai Manoj Pudukotai Dinakarrao

From top experts in biology education comes this definitive guide to the human body, published in partnership with the Royal Society of Biology.In Your Expert Guide: The Human Body, discover the many systems and surprising skills of the human body, from your astounding brain at the very top of your body, to the tiny bones in your feet built for walking. Explore the powerful organs and the jobs they do to get a clear picture of how your body works, and how you can look after it.Written by Tom Jackson and Liam Cini-O''Dwyer and published in partnership with The Royal Society of Biology. With immersive artwork by Ola Szpunar, biology comes alive for curious readers aged 8+.Books in the Your Expert Guide series: With Royal Society of Chemistry: The Periodic Table / Chemistry for Young ScientistsWith Royal Society of Biology: The Human Body / Biology for Young ScientistsWith Institute of Physics: The Universe / Physics for Young Scientists

Objev podobné jako Your Expert Guide: The Human Body for Young Scientists - Tom Jackson, Liam Cini-O'Dwyer

Familiarize yourself with the basics of Python for engineering and scientific computations using this concise, practical tutorial that is focused on writing code to learn concepts. Introduction to Python is useful for industry engineers, researchers, and students who are looking for open-source solutions for numerical computation. In this book you will learn by doing, avoiding technical jargon, which makes the concepts easy to learn. First you''ll see how to run basic calculations, absorbing technical complexities incrementally as you progress toward advanced topics. Throughout, the language is kept simple to ensure that readers at all levels can grasp the concepts. What You''ll Learn Understand the fundamentals of the Python programming language Apply Python to numerical computational programming projects in engineering and science Discover the Pythonic way of life Apply data types, operators, and arrays Carry out plotting for visualization Work with functions and loops Who This Book Is For Engineers, scientists, researchers, and students who are new to Python. Some prior programming experience would be helpful but not required.

Objev podobné jako Introduction to Python for Engineers and Scientists - Sandeep Nagar

An introduction to the Bayesian approach to statistical inference that demonstrates its superiority to orthodox frequentist statistical analysis.This book offers an introduction to the Bayesian approach to statistical inference, with a focus on nonparametric and distribution-free methods. It covers not only well-developed methods for doing Bayesian statistics but also novel tools that enable Bayesian statistical analyses for cases that previously did not have a full Bayesian solution. The book''s premise is that there are fundamental problems with orthodox frequentist statistical analyses that distort the scientific process. Side-by-side comparisons of Bayesian and frequentist methods illustrate the mismatch between the needs of experimental scientists in making inferences from data and the properties of the standard tools of classical statistics.The book first covers elementary probability theory, the binomial model, the multinomial model, and methods for comparing different experimental conditions or groups. It then turns its focus to distribution-free statistics that are based on having ranked data, examining data from experimental studies and rank-based correlative methods. Each chapter includes exercises that help readers achieve a more complete understanding of the material. The book devotes considerable attention not only to the linkage of statistics to practices in experimental science but also to the theoretical foundations ... Unknown localization key: "more"

Objev podobné jako Bayesian Statistics for Experimental Scientists - Richard A Chechile

The multidisciplinary field of quantum computing strives to exploit some of the uncanny aspects of quantum mechanics to expand our computational horizons. Quantum Computing for Computer Scientists takes readers on a tour of this fascinating area of cutting-edge research. Written in an accessible yet rigorous fashion, this book employs ideas and techniques familiar to every student of computer science. The reader is not expected to have any advanced mathematics or physics background. After presenting the necessary prerequisites, the material is organized to look at different aspects of quantum computing from the specific standpoint of computer science. There are chapters on computer architecture, algorithms, programming languages, theoretical computer science, cryptography, information theory, and hardware. The text has step-by-step examples, more than two hundred exercises with solutions, and programming drills that bring the ideas of quantum computing alive for today''s computer science students and researchers.

Objev podobné jako Quantum Computing for Computer Scientists - Noson S. Yanofsky, Mirco A. Mannucci

Pursuing a career in biomedical research can be daunting, considering the stiffer competition and uncertain career prospects in academia. This book summarizes career advice gathered during in-depth interviews with 106 biomedical scientists who lead their own laboratories. The participating principal investigators are from 44 research institutions in 11 countries. This book is unique in that it provides a glimpse into the mindset of principal investigators. Here, the reader will learn about common thought patterns and values, as well as the range of opinions and ways of thinking to be found among a large group of active principal investigators – without having to read more than a hundred individual autobiographies.The book will benefit all PhD students who want to learn more about their supervisor’s mindset in order to successfully complete their projects. It can help freshly graduated PhDs planning to pursue an academic career, and MDs contemplating a career in research, to decide whether they truly want to embark on this path. Lastly, it can offer young principal investigators a source of inspiration on how to succeed and achieve their goals.

Objev podobné jako Career Advice for Young Scientists in Biomedical Research - Bela Z. Schmidt

Explore science’s biggest unsolved mysteries, from unanswered questions about the animal kingdom and the human body to the unknowns of space and time. Have you ever wondered how the universe will end or why we dream? From the possibility of life on other planets to understanding why woolly mammoths went extinct, this science book for kids aged 7-9 sheds light on fascinating questions that are still unanswered. With stunning facts and fun science, Things Science Doesn't Know Yet is packed with the latest scientific developments and captivating topics such as the dinosaurs and time travel. Young readers will not only marvel at what science is yet to solve, but also learn how the scientific process works - step by step - through experiments, collaboration, and persistence. In this unsolved mysteries book for kids, you’ll discover:Fun, fact-packed explorations of questions including ‘why do we dream?’ and ‘could we live on other planets?’Inspiring insights that encourage children to think like scientists. Expertise from a leading science educator at the UK’s Royal Institution. Perfect for budding scientists or kids who are curious about the world, it’s the ultimate guide to the mysteries that keep scientists awake at night!

Objev podobné jako Things Scientists Don't Know Yet - Peter Gallivan

Learn how to use R to turn data into insight, knowledge, and understanding. Ideal for current and aspiring data scientists, this book introduces you to doing data science with R and RStudio, as well as the tidyverse-a collection of R packages designed to work together to make data science fast, fluent, and fun. Even if you have no programming experience, this updated edition will have you doing data science quickly.You'll learn how to import, transform, and visualize your data and communicate the results. And you'll get a complete, big-picture understanding of the data science cycle and the basic tools you need to manage the details. Each section in this edition includes exercises to help you practice what you've learned along the way.Updated for the latest tidyverse best practices, new chapters dive deeper into visualization and data wrangling, show you how to get data from spreadsheets, databases, and websites, and help you make the most of new programming tools. You'll learn how to:Visualize-create plots for data exploration and communication of resultsTransform-discover types of variables and the tools you can use to work with themImport-get data into R and in a form convenient for analysisProgram-learn R tools for solving data problems with ... Unknown localization key: "more"

Objev podobné jako R for Data Science - Grolemund Garrett, Hadley Wickham, Mine Cetinkaya-Rundel

Let Python do the heavy lifting for you as you analyze large datasets Python for Data Science For Dummies lets you get your hands dirty with data using one of the top programming languages. This beginner’s guide takes you step by step through getting started, performing data analysis, understanding datasets and example code, working with Google Colab, sampling data, and beyond. Coding your data analysis tasks will make your life easier, make you more in-demand as an employee, and open the door to valuable knowledge and insights. This new edition is updated for the latest version of Python and includes current, relevant data examples. Get a firm background in the basics of Python coding for data analysisLearn about data science careers you can pursue with Python coding skillsIntegrate data analysis with multimedia and graphics Manage and organize data with cloud-based relational databasesPython careers are on the rise. Grab this user-friendly Dummies guide and gain the programming skills you need to become a data pro.

Objev podobné jako Python for Data Science For Dummies - John Paul Mueller, Luca Massaron

A single-volume reference on data science techniques for evaluating and solving business problems using Applied Machine Learning (ML). Applied Machine Learning for Data Science Practitioners offers a practical, step-by-step guide to building end-to-end ML solutions for real-world business challenges, empowering data science practitioners to make informed decisions and select the right techniques for any use case. Unlike many data science books that focus on popular algorithms and coding, this book takes a holistic approach. It equips you with the knowledge to evaluate a range of techniques and algorithms. The book balances theoretical concepts with practical examples to illustrate key concepts, derive insights, and demonstrate applications. In addition to code snippets and reviewing output, the book provides guidance on interpreting results. This book is an essential resource if you are looking to elevate your understanding of ML and your technical capabilities, combining theoretical and practical coding examples. A basic understanding of using data to solve business problems, high school-level math and statistics, and basic Python coding skills are assumed. Written by a recognized data science expert, Applied Machine Learning for Data Science Practitioners covers essential topics, including: Data Science Fundamentals that provide you with an overview of core concepts, laying the ... Unknown localization key: "more"

Objev podobné jako Applied Machine Learning for Data Science Practitioners - Vidya Subramanian

Graphs are the natural way to understand connected data. This book explores the most important algorithms and techniques for graphs in data science, with practical examples and concrete advice on implementation and deployment. In Graph Algorithms for Data Science you will learn: Labeled-property graph modeling Constructing a graph from structured data such as CSV or SQL NLP techniques to construct a graph from unstructured data Cypher query language syntax to manipulate data and extract insights Social network analysis algorithms like PageRank and community detection How to translate graph structure to a ML model input with node embedding models Using graph features in node classification and link prediction workflows Graph Algorithms for Data Science is a hands-on guide to working with graph-based data in applications like machine learning, fraud detection, and business data analysis. It''s filled with fascinating and fun projects, demonstrating the ins-and-outs of graphs. You''ll gain practical skills by analyzing Twitter, building graphs with NLP techniques, and much more. You don''t need any graph experience to start benefiting from this insightful guide. These powerful graph algorithms are explained in clear, jargon-free text and illustrations that makes them easy to apply to your own projects. about the technology Graphs reveal ... Unknown localization key: "more"

Objev podobné jako Graph Algorithms for Data Science - Bratanic Tomaz

The R language is widely used by statisticians for data analysis, and the popularity of R programming has therefore increased substantially in recent years. The emerging Internet of Things (IoT) gathers increasing amounts of data that can be analyzed to gain useful insights into trends.R for Data Analysis in easy steps, 2nd edition has an easy-to-follow style that will appeal to anyone who wants to produce graphic visualizations to gain insights from gathered data. The book begins by explaining core programming principles of the R programming language, which stores data in “vectors” from which simple graphs can be plotted. Next, it describes how to create “matrices” to store and manipulate data from which graphs can be plotted to provide better insights. This book then demonstrates how to create “data frames” from imported data sets, and how to employ the “Grammar of Graphics” to produce advanced visualizations that can best illustrate useful insights from your data.R for Data Analysis in easy steps, 2nd edition contains separate chapters on the major features of the R programming language. There are complete example programs that demonstrate how to create Line graphs, Bar charts, Histograms, Scatter graphs, Box plots, and more. The code for each ... Unknown localization key: "more"

Objev podobné jako R for Data Analysis in easy steps - Mike McGrath

Data science and machine learning—two of the world''s hottest fields—are attracting talent from a wide variety of technical, business, and liberal arts disciplines. Python, the world''s #1 programming language, is also the most popular language for data science and machine learning. This is the first guide specifically designed to help students with widely diverse backgrounds learn foundational Python so they can use it for data science and machine learning. This book is catered to introductory-level college courses on data science. Leading data science instructor and practitioner Kennedy Behrman first walks through the process of learning to code for the first time with Python and Jupyter notebook, then introduces key libraries every Python data science programmer needs to master. Once students have learned these foundations, Behrman introduces intermediate and applied Python techniques for real-world problem-solving. Throughout, Foundational Python for Data Science presents hands-on exercises, learning assessments, case studies, and more—all created with Colab (Jupyter compatible) notebooks, so students can execute all coding examples interactively without installing or configuring any software.

Objev podobné jako Foundational Python for Data Science - Kennedy Behrman

Get the definitive handbook for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.10 and pandas 1.4, the third edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You'll learn the latest versions of pandas, NumPy, and Jupyter in the process.Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It's ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub.Use the Jupyter notebook and IPython shell for exploratory computingLearn basic and advanced features in NumPyGet started with data analysis tools in the pandas libraryUse flexible tools to load, clean, transform, merge, and reshape dataCreate informative visualizations with matplotlibApply the pandas groupby facility to slice, dice, and summarize datasetsAnalyze and manipulate regular and irregular time series dataLearn how to solve real-world data analysis problems with thorough, detailed examples

Objev podobné jako Python for Data Analysis 3e - Wes McKinney

Fast Python for Data Science is a hands-on guide to writing Python code that can process more data, faster, and with less resources. It takes a holistic approach to Python performance, showing you how your code, libraries, and computing architecture interact and can be optimized together. Written for experienced practitioners, Fast Python for Data Science dives right into practical solutions for improving computation and storage efficiency. You''ll experiment with fun and interesting examples such as rewriting games in lower-level Cython and implementing a MapReduce framework from scratch. Finally, you''ll go deep into Python GPU computing and learn how modern hardware has rehabilitated some former antipatterns and made counterintuitive ideas the most efficient way of working. About the technologyFast, accurate systems are vital for handling the huge datasets and complex analytical algorithms that are common in modern data science. Python programmers need to boost performance by writing faster pure-Python programs, optimizing the use of libraries, and utilizing modern multi-processor hardware; Fast Python for Data Science shows you how.

Objev podobné jako Fast Python for Data Science - Tiago Antao

When you know the cause of an event, you can affect its outcome. This accessible introduction to causal inference shows you how to determine causality and estimate effects using statistics and machine learning.In Causal Inference for Data Science you will learn how to: Model reality using causal graphs Estimate causal effects using statistical and machine learning techniques Determine when to use A/B tests, causal inference, and machine learning Explain and assess objectives, assumptions, risks, and limitations Determine if you have enough variables for your analysis It''s possible to predict events without knowing what causes them. Understanding causality allows you both to make data-driven predictions and also intervene to affect the outcomes. Causal Inference for Data Science shows you how to build data science tools that can identify the root cause of trends and events. You''ll learn how to interpret historical data, understand customer behaviors, and empower management to apply optimal decisions.

Objev podobné jako Causal Inference for Data Science - Aleix de Villa

For junior/senior undergraduates taking probability and statistics as applied to engineering, science, or computer science. This classic text provides a rigorous introduction to basic probability theory and statistical inference, with a unique balance between theory and methodology. Interesting, relevant applications use real data from actual studies, showing how the concepts and methods can be used to solve problems in the field. This revision focuses on improved clarity and deeper understanding.

Objev podobné jako Probability & Statistics for Engineers & Scientists, Global Edition - Keying Ye, Sharon Myers, Ronald Walpole, Raymond Myers

To succeed in AI and data science, you must first master APIs. API skills are essential for AI and data science success. With this book, data scientists and software developers will gain hands-on experience developing and using APIs with the Python programming language and popular frameworks like FastAPI and StreamLit.

Objev podobné jako Hands-On APIs for AI and Data Science - Ryan Day

Maximise student engagement and understanding of matrix methods in data-driven applications with this modern teaching package. Students are introduced to matrices in two preliminary chapters, before progressing to advanced topics such as the nuclear norm, proximal operators and convex optimization. Highlighted applications include low-rank approximation, matrix completion, subspace learning, logistic regression for binary classification, robust PCA, dimensionality reduction and Procrustes problems. Extensively classroom-tested, the book includes over 200 multiple-choice questions suitable for in-class interactive learning or quizzes, as well as homework exercises (with solutions available for instructors). It encourages active learning with engaging ''explore'' questions, with answers at the back of each chapter, and Julia code examples to demonstrate how the mathematics is actually used in practice. A suite of computational notebooks offers a hands-on learning experience for students. This is a perfect textbook for upper-level undergraduates and first-year graduate students who have taken a prior course in linear algebra basics.

Objev podobné jako Linear Algebra for Data Science, Machine Learning, and Signal Processing - Jeffrey A. Fessler, Raj Rao Nadakuditi

Learn how to use Python and associated data-science libraries to work with and visualize vectors and matrices and their operations, as well import data to apply these techniques. Learn basics of performing vector and matrix operations by hand, how to use several different Python libraries for performing operations.

Objev podobné jako Linear Algebra for Data Science with Python - John M. Shea

Learn data science with Python by building five real-world projects! In Data Science Bookcamp you’ll test and build your knowledge of Python and learn to handle the kind of open-ended problems that professional data scientists work on daily. Downloadable data sets and thoroughly-explained solutions help you lock in what you’ve learned, building your confidence and making you ready for an exciting new data science career. about the technologyIn real-world practice, data scientists create innovative solutions to novel open ended problems. Easy to learn and use, the Python language has become the de facto language for data science amongst researchers, developers, and business users. But knowing a few basic algorithms is not enough to tackle a vague and thorny problem. It takes relentless practice at cracking difficult data tasks to achieve mastery in the field. That’s just what this book delivers. about the book Data Science Bookcamp is a comprehensive set of challenging projects carefully designed to grow your data science skills from novice to master. Veteran data scientist Leonard Apeltsin sets five increasingly difficult exercises that test your abilities against the kind of problems you’d encounter in the real world. As you solve each challenge, you’ll acquire and expand the ... Unknown localization key: "more"

Objev podobné jako Data Science Bookcamp - Leonard Apeltsin

Great data presentations tell a story. Learn how to organize, visualize, and present data using Python, generative AI, and the cutting-edge Altair data analysis toolkit.After you''ve crunched, sliced, and organized your data behind the scenes, you need to present it in a way that tells a story. With Python''s Altair library and generative AI tools like Copilot and ChatGPT, it''s never been easier to create intuitive data presentations.In Data Storytelling with Generative AI you''ll discover: Using Python Altair for data visualization Using Generative AI tools for data storytelling The main concepts of data storytelling Building data stories with the DIKW pyramid approach Transforming raw data into a data story Data Storytelling with Generative AI teaches you how to turn raw data into effective, insightful data stories. You''ll learn exactly what goes into an effective data story, then combine your Python data skills with the Altair library and AI tools to rapidly create amazing visualizations. Your bosses and decision-makers will love your new presentations—and you''ll love how quick Generative AI makes the whole process!

Objev podobné jako Data Storytelling with Generative AI - Angelica Duca

With the advent of such advanced technologies as cloud computing, the Internet of Things, the Medical Internet of Things, the Industry Internet of Things and sensor networks as well as the exponential growth in the usage of Internet-based and social media platforms, there are enormous oceans of data. These huge volumes of data can be used for effective decision making and improved performance if analyzed properly. Due to its inherent characteristics, big data is very complex and cannot be handled and processed by traditional database management approaches. There is a need for sophisticated approaches, tools and technologies that can be used to store, manage and analyze these enormous amounts of data to make the best use of them.Big Data Concepts, Technologies, and Applications covers the concepts, technologies, and applications of big data analytics. Presenting the state-of-the-art technologies in use for big data analytics. it provides an in-depth discussion about the important sectors where big data analytics has proven to be very effective in improving performance and helping industries to remain competitive. This book provides insight into the novel areas of big data analytics and the research directions for the scholars working in the domain. Highlights include:The advantages, disadvantages and challenges ... Unknown localization key: "more"

Objev podobné jako Big Data Concepts, Technologies, and Applications - Mohammad Shahid Husain, Tamanna Siddiqui, Mohammad Zunnun Khan

The past two decades have seen an explosion both in the volume of data we use, and our understanding of its management.However, while techniques and technology for manipulating data have advanced rapidly in this time, the concepts around the value of our data have not. This lack of progress has made it increasingly difficult for organisations to understand the value in their data, the value of their data and how exploit that value. Halo Data proposes a paradigm shift in methodology for organisations to properly appreciate and leverage the value of their data. Written by an author team with many years’ experience in data strategy, management and technology, the book will first review the current state of our understanding of data. This opening will demonstrate the limitations of this status quo, including a discussion on metadata and its limitations, data monetisation and data-driven business models. Following this, the book will present a new concept and framework for understanding and quantifying value in an organisation’s data and a practical methodology for using this in practice.Ideal for data leaders and executives who are looking to leverage the data at their fingertips.

Objev podobné jako Halo Data - Peter Jackson, Caroline Carruthers

Become well-versed with data engineering concepts and exam objectives to achieve Azure Data Engineer Associate certificationKey FeaturesUnderstand and apply data engineering concepts to real-world problems and prepare for the DP-203 certification examExplore the various Azure services for building end-to-end data solutionsGain a solid understanding of building secure and sustainable data solutions using Azure servicesBook DescriptionAzure is one of the leading cloud providers in the world, providing numerous services for data hosting and data processing. Most of the companies today are either cloud-native or are migrating to the cloud much faster than ever. This has led to an explosion of data engineering jobs, with aspiring and experienced data engineers trying to outshine each other. Gaining the DP-203: Azure Data Engineer Associate certification is a sure-fire way of showing future employers that you have what it takes to become an Azure Data Engineer. This book will help you prepare for the DP-203 examination in a structured way, covering all the topics specified in the syllabus with detailed explanations and exam tips. The book starts by covering the fundamentals of Azure, and then takes the example of a hypothetical company and walks you through the various stages of building data engineering solutions. Throughout ... Unknown localization key: "more"

Objev podobné jako Azure Data Engineer Associate Certification Guide - Newton Alex

Written by over 120 data management practitioners, this is the most impressive compilation of data management principals and best practices, ever assembled. It provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure. The equivalent of the PMBOK or the BABOK, the DAMA-DMBOK provides information on: Data Governance; Data Architecture Management; Data Development; Database Operations Management; Data Security Management; Reference & Master Data Management; Data Warehousing & Business Intelligence Management; Document & Content Management; Meta Data Management; Data Quality Management; Professional Development. As an authoritative introduction to data management, the goals of the DAMA-DMBOK Guide are: To build consensus for a generally applicable view of data management functions; To provide standard definitions for commonly used data management functions, deliverables, roles, and other terminology; To document guiding principles for data management; To present a vendor-neutral overview to commonly accepted good practices, widely adopted methods and techniques, and significant alternative approaches; To clarify the scope and boundaries of data management; To act as a reference which guides readers to additional resources for further understanding.

Objev podobné jako DAMA-DMBOK Guide

An Absolute Beginner''s Guide to Learning Data Analysis Using Python, a Demanding Skill for TodayKey FeaturesHands-on learning experience of Python''s fundamentals.Covers various examples of how to code end-to-end data analysis with easy illustrations.An excellent starting point to begin your data analysis journey with Python programming.DescriptionIn an effort to provide content for beginners, the book Data Analysis with Python provides a concrete first step in learning data analysis. Written by a data professional with decades of experience, this book provides a solid foundation in data analysis and numerous data science processes. In doing so, readers become familiar with common Python libraries and straightforward scripting techniques.Python and many of its well-known data analysis libraries, such as Pandas, NumPy, and Matplotlib, are utilized throughout this book to carry out various operations typical of data analysis projects.Following an introduction to Python programming fundamentals, the book combines well-known numerical calculation and statistical libraries to demonstrate the fundamentals of programming, accompanied by many practical examples. This book provides a solid groundwork for data analysis by teaching Python programming as well as Python''s built-in data analysis capabilities.What you will learnLearn the fundamentals of core Python programming for data analysis.Master Python''s most demanding data analysis and visualization libraries, ... Unknown localization key: "more"

Objev podobné jako Data Analysis with Python - Rituraj Dixit

For thirty years, “best practices” in data have delivered bigger platforms, thicker slide decks, and disappointing outcomes. The problem isn’t technology. It’s mindset. The Data Hero Playbook reveals how limiting beliefs—learned helplessness, all-or-nothing thinking, externalized blame—have kept data from becoming truly transformational. The cure is a growth mindset, put into action through practical steps any data professional can take. You’ll discover how to: Put customers at the center of every decision. Apply product management principles to data work. Quantify value in revenue, cost savings, and risk reduction. Run data as if it were a P&L. Deliver fast wins with a Data Strategy MVP in weeks, not months. Unflinching about what hasn’t worked yet unapologetically hopeful about what’s next, this book is a call to arms for data leaders ready to escape the status quo. If you want to stop explaining why data should matter and start proving it with measurable results, The Data Hero Playbook is your guide. Become the data hero your company actually needs.

Objev podobné jako The Data Hero Playbook - Malcolm Hawker

This book provides insights into the true nature of financial and economic data, and is a practical guide on how to analyze a variety of data sources. The focus of the book is on finance and economics, but it also illustrates the use of quantitative analysis and data science in many different areas. Lastly, the book includes practical information on how to store and process data and provides a framework for data driven reasoning about the world.The book begins with entertaining tales from Graham Giller''s career in finance, starting with speculating in UK government bonds at the Oxford Post Office, accidentally creating a global instant messaging system that went ''viral'' before anybody knew what that meant, on being the person who forgot to hit ''enter'' to run a hundred-million dollar statistical arbitrage system, what he decoded from his brief time spent with Jim Simons, and giving Michael Bloomberg a tutorial on Granger Causality.The majority of the content is a narrative of analytic work done on financial, economics, and alternative data, structured around both Dr Giller''s professional career and some of the things that just interested him. The goal is to stimulate interest in predictive methods, to give accurate characterizations of ... Unknown localization key: "more"

Objev podobné jako Adventures In Financial Data Science: The Empirical Properties Of Financial And Economic Data - Graham L Giller

This book provides the tools, the methods, and the theory to meet the challenges of contemporary data science applied to geographic problems and data. In the new world of pervasive, large, frequent, and rapid data, there are new opportunities to understand and analyze the role of geography in everyday life. Geographic Data Science with Python introduces a new way of thinking about analysis, by using geographical and computational reasoning, it shows the reader how to unlock new insights hidden within data.Key Features:● Showcases the excellent data science environment in Python.● Provides examples for readers to replicate, adapt, extend, and improve.● Covers the crucial knowledge needed by geographic data scientists.It presents concepts in a far more geographic way than competing textbooks, covering spatial data, mapping, and spatial statistics whilst covering concepts, such as clusters and outliers, as geographic concepts.Intended for data scientists, GIScientists, and geographers, the material provided in this book is of interest due to the manner in which it presents geospatial data, methods, tools, and practices in this new field.

Objev podobné jako Geographic Data Science with Python - Dani Arribas-Bel, Sergio Rey, Levi John Wolf

All data are the result of human actions whether by experimentations, observations, or declarations. As such, the presumption of knowing what data are about is subject to imperfections that can affect the validity of research efforts. With calls for data-based research comes the need to assure the reliability of generated data. The reliability of converting texts into analyzable data has become a burning issue in several areas. However, this issue has been met by only a few limited, and sometimes misleading measures of the extent to which data can be trusted as surrogates of the phenomena of analytical interests. The statistic proposed by the author – "Krippendorff’s Alpha" – is widely used in the social sciences, not only where human judgements are involved but also where measurements are compared. The Reliability of Generating Data expands on the author’s seminal work in content analysis and develops methods for assessing the reliability of the kind of data that previously defied evaluations for this purpose. It opens with a discussion of the epistemology of reliable data, then presents the most basic alpha coefficient for the single-valued coding of predefined units. This largely familiar way of measuring reliability provides the platform for the succeeding ... Unknown localization key: "more"

Objev podobné jako The Reliability of Generating Data - Klaus Krippendorff

Digital transformation and data projects are not new and yet, for many, they are a challenge. Driving Data Projects is a compelling guide that empowers data teams and professionals to navigate the complexities of data projects, fostering a more data-informed culture within their organizations.With practical insights and step-by-step methodologies, this guide provides a clear path how to drive data projects effectively in any organization, regardless of its sector or maturity level whilst also demonstrating how to overcome the overwhelming feelings of where to start and how to not lose momentum. This book offers the keys to identifying opportunities for driving data projects and how to overcome challenges to drive successful data initiatives.Driving Data Projects is highly practical and provides reflections, worksheets, checklists, activities, and tools making it accessible to students new to driving data projects and culture change. This book is also a must-have guide for data teams and professionals committed to unleashing the transformative power of data in their organizations.

Objev podobné jako Driving Data Projects - Christine Haskell

"Data Mesh: Principles, patterns, architecture, and strategies for data-driven decision making" introduces Data Mesh which is a macro data architecture pattern designed to harmonize governance with flexibility. This book guides readers through the nuances of Data Mesh topologies, explaining how they can be tailored to meet specific organizational needs while balancing central control with domain-specific autonomy. The book delves into the Data Mesh governance framework, which provides a structured approach to manage and control decentralized data assets effectively. It emphasizes the importance of a well-implemented governance structure that ensures data quality, compliance, and access control across various domains. Additionally, the book outlines robust data cataloging and sharing strategies, enabling organizations to improve data discoverability, usage, and interoperability between cross-functional teams. Securing Data Mesh architectures is another critical focus. The text explores comprehensive security strategies that protect data across different layers of the architecture, ensuring data integrity and protecting against breaches.

Objev podobné jako Data Mesh - Pradeep Menon

In today''s data-driven world, the ability to extract meaningful insights from vast datasets is crucial for success in various fields. This ultimate book for mastering open-source libraries of data science in Python equips you with the essential tools and techniques to navigate the ever-evolving field of data analysis and visualization. Discover how to use Python libraries like NumPy, Pandas, and Matplotlib for data manipulation, analysis, and visualization. This book also covers scientific computing with SciPy and integrates ChatGPT to boost your data science workflow. Designed for data scientists, analysts, and beginners, it offers a practical, hands-on approach to mastering data science fundamentals. With real-world applications and exercises, you will turn raw data into actionable insights, gaining a competitive edge. This book covers everything you need, including open-source libraries, Visual Explorer tools, and ChatGPT, making it a one-stop resource for Python-based data science.

Objev podobné jako Ultimate Data Science Programming in Python - Saurabh Chandrakar