linear algebra for data science with python john m shea

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

Foundations of Data Science with Python introduces readers to the fundamentals of data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. This book is targeted toward engineers and scientists, but it should be readily understandable to anyone who knows basic calculus and the essentials of computer programming. It uses a computational-first approach to data science: the reader will learn how to use Python and the associated data-science libraries to visualize, transform, and model data, as well as how to conduct statistical tests using real data sets. Rather than relying on obscure formulas that only apply to very specific statistical tests, this book teaches readers how to perform statistical tests via resampling; this is a simple and general approach to conducting statistical tests using simulations that draw samples from the data being analyzed. The statistical techniques and tools are explained and demonstrated using a diverse collection of data sets to conduct statistical tests related to contemporary topics, from the effects of socioeconomic factors on the spread of the COVID-19 virus to the impact of state laws on firearms mortality.This book can be used as an undergraduate textbook for an Introduction to Data Science course or to provide a ... Unknown localization key: "more"

Objev podobné jako Foundations of Data Science with Python - John M. Shea

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

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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

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

Develop a practical understanding of data science with this hands-on textbook for introductory courses. This new edition is fully revised and updated, with an exclusive focus on the popular data science tool Python. The book includes many examples of real-life applications, with practice ranging from small to big data.

Objev podobné jako A Hands-On Introduction to Data Science with Python - Chirag Shah

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

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.

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This book developed from the need to teach a linear algebra course to students focused on data science and bioinformatics programs. These students tend not to realize the importance of linear algebra in applied sciences, since traditional linear algebra courses tend to cover mathematical contexts but not the computational aspect of linear algebra or its applications to data science and bioinformatics. The author presents the topics in a traditional course, yet offers lectures as well as lab exercises on simulated and empirical data sets. This textbook provides students a theoretical basis which can then be applied to the practical R and Python problems, providing the tools needed for real-world applications.Each section starts with working examples to demonstrate how tools from linear algebra can help solve problems in applied sciences. These exercises start from easy computations, such as computing determinants of matrices, to practical applications on simulated and empirical data sets with R so that students learn how to get started with R, along with computational examples in each section, and then students learn how to apply what they''ve learned to problems in applied sciences.This book is designed from first principles to demonstrate the importance of linear algebra through working computational ... Unknown localization key: "more"

Objev podobné jako Linear Algebra and Its Applications with R - Ruriko Yoshida

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

Linear Algebra For Dummies serves as an easy-to-follow guide that introduces (or re-introduces) readers to key concepts such as matrices, vector spaces, and eigenvalues and eigenvectors. It presents the information in a way that allows readers to fully digest not just the "how" of solving linear algebraic problems, but also the "why.

Objev podobné jako Linear Algebra For Dummies - Mary Jane Sterling

This book is intended to serve as a bridge in statistics for graduates and business practitioners interested in using their skills in the area of data science and analytics as well as statistical analysis in general. On the one hand, the book is intended to be a refresher for readers who have taken some courses in statistics, but who have not necessarily used it in their day-to-day work. On the other hand, the material can be suitable for readers interested in the subject as a first encounter with statistical work in Python. Statistics and Data Visualisation with Python aims to build statistical knowledge from the ground up by enabling the reader to understand the ideas behind inferential statistics and begin to formulate hypotheses that form the foundations for the applications and algorithms in statistical analysis, business analytics, machine learning, and applied machine learning. This book begins with the basics of programming in Python and data analysis, to help construct a solid basis in statistical methods and hypothesis testing, which are useful in many modern applications.

Objev podobné jako Statistics and Data Visualisation with Python - Jesus Rogel-Salazar

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

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

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

From a review of the first edition: "Modern Data Science with R… is rich with examples and is guided by a strong narrative voice. What’s more, it presents an organizing framework that makes a convincing argument that data science is a course distinct from applied statistics" (The American Statistician).Modern Data Science with R is a comprehensive data science textbook for undergraduates that incorporates statistical and computational thinking to solve real-world data problems. Rather than focus exclusively on case studies or programming syntax, this book illustrates how statistical programming in the state-of-the-art R/RStudio computing environment can be leveraged to extract meaningful information from a variety of data in the service of addressing compelling questions.The second edition is updated to reflect the growing influence of the tidyverse set of packages. All code in the book has been revised and styled to be more readable and easier to understand. New functionality from packages like sf, purrr, tidymodels, and tidytext is now integrated into the text. All chapters have been revised, and several have been split, re-organized, or re-imagined to meet the shifting landscape of best practice.

Objev podobné jako Modern Data Science with R - Benjamin S. Baumer, Nicholas J. Horton, Daniel T. Kaplan

Statistical Analytics for Health Data Science with SAS and R Set compiles fundamental statistical principles with advanced analytical techniques and covers a wide range of statistical methodologies. With an emphasis on real-world applications, it integrates publicly available health datasets and provides case studies.

Objev podobné jako Statistical Analytics for Health Data Science with SAS and R Set - Jeffrey Wilson, Ding-Geng Chen, Karl E. Peace

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

A fast-paced introduction to Python for intermediate developers–now with coverage of generative AI!For over 25 years, The Quick Python Book has been one of the best Python books money can buy. It concisely covers programming basics, while introducing Python''s comprehensive standard library and unique features in depth and detail. In this fourth edition, you''ll find new coverage of AI coding tools like Copilot and Google''s Colaboratory (Colab), and develop a mindset that can make the most of AI. The Quick Python Book, Fourth Edition includes: Python syntax, data structures, and best practices Python as an object oriented language Common Python libraries Basic data handling with Python Using AI code generation tools with Python Whether you''re new to Python or looking to advance your basic skills, The Quick Python Book, Fourth Edition will get you writing effective Python code fast. Python authority and former Chair of the Python Software Foundation Board or Directors Naomi Ceder has returned to author this extensively revised fourth edition. With the personal touch of a skilled teacher, Naomi beautifully balances details of the language with the insights and advice you need to handle any task. About the technology: System automation. High-performance web apps. Cloud and back-end ... Unknown localization key: "more"

Objev podobné jako The Quick Python Book, Fourth Edition - Naomi Ceder

You Will Learn Python! Zed Shaw has created the world''s most reliable system for learning Python. Follow it and you will succeed--just like the millions of beginners Zed has taught to date! You bring the discipline, persistence, and attention; the author supplies the masterful knowledge you need to succeed. In Learn Python the Hard Way, Fifth Edition, you''ll learn Python by working through 60 lovingly crafted exercises. Read them. Type in the code. Run it. Fix your mistakes. Repeat. As you do, you''ll learn how a computer works, how to solve problems, and how to enjoy programming . . . even when it''s driving you crazy. Install a complete Python environment Organize and write code Fix and break code Basic mathematics Strings and text Interact with users Work with files Looping and logic Object-oriented programming Data structures using lists and dictionaries Modules, classes, and objects Python packaging Automated testing Basic SQL for Data Science Web scraping Fixing bad data (munging) The "Data" part of "Data Science" It''ll be frustrating at first. But if you keep trying, you''ll get it--and it''ll feel amazing! This course will reward you for every minute you put into it. Soon, you''ll know one of the ... Unknown localization key: "more"

Objev podobné jako Learn Python the Hard Way - Zed Shaw

Kniha - autor Eric Matthes, 544 stran, anglicky, brožovaná bez přebalu matná Python Crash Course is the world’s bestselling programming book, with over 1,500,000 copies sold to date! Python Crash Course is the world’s best-selling guide to the Python programming language. This fast-paced, thorough introduction will have you writing programs, solving problems, and developing functioning applications in no time. You’ll start by learning basic programming concepts, such as variables, lists, classes, and loops, and practice writing clean code with exercises for each topic. You’ll also learn how to make your programs interactive and test your code safely before adding it to a project. You’ll put your new knowledge into practice by creating a Space Invaders–inspired arcade game, building a set of data visualizations with Python’s handy libraries, and deploying a simple application online. As you work through the book, you’ll learn how to: Use powerful Python...

Objev podobné jako Python Crash Course: 3rd Edition (9781718502703)

Prepares students for Microsoft Exam 70-774-and helps them demonstrate real-world mastery of performing key data science activities with Azure Machine Learning services. Designed for experienced IT students ready to advance their status, Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the MCSA level.

Objev podobné jako Exam Ref 70-774 Perform Cloud Data Science with Azure Machine Learning - Ginger Grant, Tamanaco Francisquez, Pau Sempere, Paco Gonzalez, Julio Granado

For sophomore-level orjunior/senior-level first courses in linear algebra; assumes calculus as aprerequisite. A thorough and accessibleintroduction to linear algebra. The new 10thEdition of Linear Algebra with Applications continuesto encourage a challenging and broad understanding of the subject. For thisedition, Steven Leon—one of the leading figures in the use of technology forlinear algebra—is joined by new co-author Lisette de Pillis of Harvey MuddCollege, who brings her passion for teaching and solving real-world problems tothis revision. Each chapter contains integratedworked examples, practical applications, computer exercises, and chapter tests. The important roles played by geometry and visualization in understandinglinear algebra are emphasized.

Objev podobné jako Linear Algebra with Applications, Global Edition - Lisette Pillis, Steven Leon

This book provides a comprehensive knowledge of linear algebra for graduate and undergraduate courses. As a self-contained text, it aims at covering all important areas of the subject, including algebraic structures, matrices and systems of linear equations, vector spaces, linear transformations, dual and inner product spaces, canonical, bilinear, quadratic, sesquilinear, Hermitian forms of operators and tensor products of vector spaces with their algebras. The last three chapters focus on empowering readers to pursue interdisciplinary applications of linear algebra in numerical methods, analytical geometry and in solving linear system of differential equations. A rich collection of examples and exercises are present at the end of each section to enhance the conceptual understanding of readers. Basic knowledge of various notions, such as sets, relations, mappings, etc., has been pre-assumed.

Objev podobné jako Advanced Linear Algebra with Applications - Mohammad Ashraf, Vincenzo De Filippis, Mohammad Aslam Siddeeque

This brilliant CGP book is the perfect no-nonsense guide for anyone who wants to learn Python. It contains clear notes on all the key programming skills - ideal for Python beginners, GCSE Computer Science students, and as an introduction to Python at A-Level. There are plenty of useful practice questions, fully-worked examples and coding challenges throughout, with full answers included at the back of the book. We've even added over 250 downloadable files covering different areas of Python - they're just the ticket for anyone looking for practical, on-screen practice. If that wasn't enough, there are video solutions to walk you through some of the coding challenges and we've also included a free Online Edition of the entire book - just use the unique code printed inside the cover to gain access. Don't miss our matching Python Programming Cards (9781837741380) to become a real Python pro!

Objev podobné jako Python Programming Guide for GCSE Computer Science with Online Edition, Python Files & Videos - CGP Books

Reiji wants two things in life: a black belt in karate and Misa, the girl of his dreams. Luckily, Misa's big brother is the captain of the university karate club and is ready to strike a deal: Reiji can join the club if he tutors Misa in linear algebra. Follow along in The Manga Guide to Linear Algebra as Reiji takes Misa from the absolute basics of this tricky subject through mind-bending operations like performing linear transformations, calculating determinants, and finding eigenvectors and eigenvalues. With memorable examples like miniature golf games and karate tournaments, Reiji transforms abstract concepts into something concrete, understandable, and even fun. As you follow Misa through her linear algebra crash course, you'll learn about: Basic vector and matrix operations such as addition, subtraction, and multiplication Linear dependence, independence, and bases Using Gaussian elimination to calculate inverse matrices Subspaces, dimension, and linear span Practical applications of linear algebra in fields like computer graphics, cryptography, and engineering But Misa's brother may get more than he bargained for as sparks start to fly between student and tutor. Will Reiji end up with the girl or just a pummeling from her oversized brother? Real math, real romance, and real action ... Unknown localization key: "more"

Objev podobné jako The Manga Guide to Linear Algebra - Shin Takahashi

Fraleigh and Beauregard''s text is known for its clear presentation and writing style, mathematical appropriateness, and overall student usability. Its inclusion of calculus-related examples, true/false problems, section summaries, integrated applications, and coverage of Cn make it a superb text for the sophomore or junior-level linear algebra course. This Third Edition retains the features that have made it successful over the years, while addressing recent developments of how linear algebra is taught and learned. Key concepts are presented early on, with an emphasis on geometry.

Objev podobné jako Linear Algebra - John B. Fraleigh, Raymond Beauregard

Learn key concepts of linear algebra to equip yourself in your studies and future career. Linear Algebra and Its Applications 6th edition by Steven R. Lay, Judi J. McDonald and David C. Lay is an excellent introductory guide to the principles and foundations of practical linear algebra. With its learner-friendly approach, the textbook starts with easier material, building confidence by introducing typically challenging concepts early on and gradually developing them. The book revisits those concepts throughout, ensuring you do not become overwhelmed when abstract concepts are introduced, as you progress with your learning. The latest edition provides new and revised content, with a range of features, including: A broad range of introductory vignettes, application examples, and online resources New material and topics to consolidate and enhance your understanding of the subject New, modernised applications to prepare your learning of the most innovative topics, such as machine learning, Artificial Intelligence, and digital signal processing With an array of exercises and questions to support your learning, this textbook provides the tools you need to build on your understanding of linear algebra and succeed in your studies. Also available with MyLab® Math MyLab is the teaching and learning platform that empowers you to ... Unknown localization key: "more"

Objev podobné jako Linear Algebra and Its Applications, Global Edition - David Lay, Steven Lay, Judi McDonald

Create simple, easy programs in the popular Python language Beginning Programming with Python For Dummies is the trusted way to learn the foundations of programming using the Python programming language. Python is one of the top-ranked languages, and there’s no better way to get started in computer programming than this friendly guide. You’ll learn the basics of coding and the process of creating simple, fun programs right away. This updated edition features new chapters, including coverage of Google Colab, plus expanded information on functions and objects, and new examples and graphics that are relevant to today’s beginning coders. Dummies helps you discover the wealth of things you can achieve with Python. Employ an online coding environment to avoid installation woes and code anywhere, any time Learn the basics of programming using the popular Python language Create easy, fun projects to show off your new coding chops Fix errors in your code and use Python with external data sets Beginning Programming with Python For Dummies will get new programmers started—the easy way.Â

Objev podobné jako Beginning Programming with Python For Dummies - John Paul Mueller

Linear algebra is a fundamental area of mathematics, and is arguably the most powerful mathematical tool ever developed. It is a core topic of study within fields as diverse as: business, economics, engineering, physics, computer science, ecology, sociology, demography and genetics. For an example of linear algebra at work, one needs to look no further than the Google search engine, which relies upon linear algebra to rank the results of a search with respect to relevance. The strength of the text is in the large number of examples and the step-by-step explanation of each topic as it is introduced. It is compiled in a way that allows distance learning, with explicit solutions to set problems freely available online. The miscellaneous exercises at the end of each chapter comprise questions from past exam papers from various universities, helping to reinforce the reader''s confidence. Also included, generally at the beginning of sections, are short historical biographies of the leading players in the field of linear algebra to provide context for the topics covered. The dynamic and engaging style of the book includes frequent question and answer sections to test the reader''s understanding of the methods introduced, rather than requiring rote learning. When ... Unknown localization key: "more"

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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

This series supports learners through the Cambridge IGCSE™ and O Level Computer Science syllabuses (0478/0984/2210). Develop skills and confidence with our programming book for Python. Created to support students undertaking the Cambridge IGCSE™ and O Level Computer Science syllabuses, this resource provides tailored support when programming with Python. A three-tiered approach to programming tasks across the book provides scaffolded support for students of all levels of understanding. Answers are accessible in the ''Solutions'' chapter in the digital part of the resource on the Cambridge GO platform, enabling students to practise their programming skills in class or at home.

Objev podobné jako Cambridge IGCSEâ„¢ and O Level Computer Science Programming Book for Python with Digital Access (2 Years) - Chris Roffey

Elementary Linear Algebra: Applications Version, 12th Edition, gives an elementary treatment of linear algebra that is suitable for a first course for undergraduate students. The classic treatment of linear algebra presents the fundamentals in the clearest possible way, examining basic ideas by means of computational examples and geometrical interpretation. It proceeds from familiar concepts to the unfamiliar, from the concrete to the abstract. Readers consistently praise this outstanding text for its expository style and clarity of presentation. In this edition, a new section has been added to describe the applications of linear algebra in emerging fields such as data science, machine learning, climate science, geomatics, and biological modeling. New exercises have been added with special attention to the expanded early introduction to linear transformations and new examples have been added, where needed, to support the exercise sets. Calculus is not a prerequisite, but there are clearly labeled exercises and examples (which can be omitted without loss of continuity) for students who have studied calculus.

Objev podobné jako Elementary Linear Algebra, Application Version, International Adaptation, Revised Edition - Howard Anton, Anton Kaul, Chris Rorres

For courses in Differential Equations and Linear Algebra. The right balance between concepts, visualization, applications, and skills Differential Equations and Linear Algebra provides the conceptual development and geometric visualization of a modern differential equations and linear algebra course that is essential to science and engineering students. It balances traditional manual methods with the new, computer-based methods that illuminate qualitative phenomena – a comprehensive approach that makes accessible a wider range of more realistic applications. The book combines core topics in elementary differential equations with concepts and methods of elementary linear algebra. It starts and ends with discussions of mathematical modeling of real-world phenomena, evident in figures, examples, problems, and applications throughout. For the first time, MyLabTM Math is available for this text, providing online homework with immediate feedback, the complete eText, and more. Additionally, new presentation slides created by author David Calvis are available in Beamer (LaTeX) and PDF formats. The slides are ideal for classroom lectures and student review, and combined with Calvis’ superlative instructional videos offer a level of support not found in any other Differential Equations course. Also available with MyLab Mathematics MyLab Mathematics is the teaching and learning platform that empowers you to reach every student. ... Unknown localization key: "more"

Objev podobné jako Differential Equations and Linear Algebra, Global Edition - C. Edwards, David Penney, David Calvis

This text focuses on the primary topics in a first course in Linear Algebra. The author includes additional advanced topics related to data analysis, singular value decomposition, and connections to differential equations. This is a lab text that would lead a class through Linear Algebra using Mathematica® demonstrations and Mathematica® coding.The book includes interesting examples embedded in the projects. Examples include the discussions of “Lights Out”, Nim, the Hill Cipher, and a variety of relevant data science projects.The 2nd Edition contains:Additional Theorems and Problems for students to prove/disprove (these act as theory exercises at the end of most sections of the text)Additional sections that support Data Analytics techniques, such as Kronecker sums and products, and LU decomposition of the Vandermonde matrixUpdated and expanded end-of-chapter projectsInstructors and students alike have enjoyed this popular book, as it offers the opportunity to add Mathematica® to the Linear Algebra course. I would definitely use the book (specifically the projects at the end of each section) to motivate undergraduate research.—Nick Luke, North Carolina A&T State University.

Objev podobné jako Exploring Linear Algebra - Crista Arangala

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

Tough Test Questions? Missed Lectures? Not Enough Time? Textbook too Pricey?Fortunately, there''s Schaum''s. This all-in-one-package includes more than 600 fully-solved problems, examples, and practice exercises to sharpen your problem-solving skills. Plus, you will have access to 25 detailed videos featuring math instructors who explain how to solve the most commonly tested problems--it''s just like having your own virtual tutor! You''ll find everything you need to build confidence, skills, and knowledge for the highest score possible.More than 40 million students have trusted Schaum''s to help them succeed in the classroom and on exams. Schaum''s is the key to faster learning and higher grades in every subject. Each Outline presents all the essential course information in an easy-to-follow, topic-by-topic format. Helpful tables and illustrations increase your understanding of the subject at hand.Schaum’s Outline of Linear Algebra, Sixth Edition features: • Updated content to match the latest curriculum• Over 600 problems with step-by-step solutions• An accessible outline format for quick and easy review• Clear explanations for all linear algebra concepts• Access to revised Schaums.com website with access to 25 problem-solving videos, and more

Objev podobné jako Schaum's Outline of Linear Algebra, Sixth Edition - Marc Lipson, Seymour Lipschutz

Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using a global airline business’s customer survey dataset to illustrate how to turn data in business decisions, in addition to numerous examples throughout. To aid in usability beyond the classroom, the text features full integration of freely-available R and RStudio software, one of the most popular data science tools available. Designed for students with little to no experience in related areas like computer science, the book chapters follow a logical order from introduction and installation of R and RStudio, working with data architecture, undertaking data collection, performing data analysis, and transitioning to data archiving and presentation. Each chapter follows a familiar structure, starting with learning objectives and background, following the basic steps of functions alongside simple examples, applying these functions to the case study, and ending with chapter challenge questions, sources, and a list of R functions so students know what to expect in each step of their data science course. Data Science for Business with ... Unknown localization key: "more"

Objev podobné jako Data Science for Business With R - Jeffrey Morgan Stanton, Jeffrey S. Saltz

Wrangle stats as you learn how to graph, analyze, and interpret data with Python Statistical Analysis with Python For Dummies introduces you to the tool of choice for digging deep into data to inform business decisions. Even if you're new to coding, this book unlocks the magic of Python and shows you how to apply it to statistical analysis tasks. You'll learn to set up a coding environment and use Python's libraries and functions to mine data for correlations and test hypotheses. You'll also get a crash course in the concepts of probability, including graphing and explaining your results. Part coding book, part stats class, part business analyst guide, this book is ideal for anyone tasked with squeezing insight from data. Get clear explanations of the basics of statistics and data analysisLearn how to summarize and analyze data with Python, step by stepImprove business decisions with objective evidence and analysisExplore hypothesis testing, regression analysis, and prediction techniques This is the perfect introduction to Python for students, professionals, and the stat-curious.

Objev podobné jako Statistical Analysis with Python For Dummies - Joseph Schmuller

Classic Computer Science Problems in Python presents dozens of coding challenges, ranging from simple tasks like finding items in a list with a binary sort algorithm to clustering data using k-means. Classic Computer Science Problems in Python deepens your Python language skills by challenging you with time-tested scenarios, exercises, and algorithms. As you work through examples in search, clustering, graphs, and more, you''ll remember important things you''ve forgotten and discover classic solutions to your "new" problems Key Features · Breadth-first and depth-first search algorithms · Constraints satisfaction problems · Common techniques for graphs · Adversarial Search · Neural networks and genetic algorithms · Written for data engineers and scientists with experience using Python. For readers comfortable with the basics of Python About the technology Python is used everywhere for web applications, data munging, and powerful machine learning applications. Even problems that seem new or unique stand on the shoulders of classic algorithms, coding techniques, and engineering principles. Master these core skills, and you’ll be ready to use Python for AI, data-centric programming, deep learning, and the other challenges you’ll face as you grow your skill as a programmer. David Kopec teaches at Champlain College in Burlington, VT and is the ... Unknown localization key: "more"

Objev podobné jako Classic Computer Science Problems in Python - David Kopec

This book introduces computing and programming with undergraduate engineering students in mind. It uses Python (Version 3) as the programming language, chosen for its simplicity, readability, wide applicability and large collection of libraries. After introducing engineering-related Python libraries, such as NumPy, Pandas, Matplotlib, Sci-kit, Programming with Python for Engineers shows how Python can be used to implement methods common in a wide spectrum of engineering-related problems drawn from (for example): design, control, decision-making, scheduling and planning. Important features of the book include the following:   The book contains interactive content for illustration of important concepts, where the user can provide input and by clicking buttons, trace through the steps. Each chapter is also accessible as a Jupyter Notebook page and every code piece is executable. This allows the readers to run code examples in chapters immediately, to make changes and gain a better grasp of the concepts presented.     The coverage of topics is complemented by illustrative examples and exercises. For instructors adopting the textbook, a solutions manual is provided at https://sites.google.com/springernature.com/extramaterial/lecturer-material.

Objev podobné jako Programming with Python for Engineers - Gokturk Ucoluk, Sinan Kalkan, Onur T. Sehitoglu

Formulas, fractions, and factoring got you down? Master the fundamentals of operations, equations, exponents, and more to score higher in Algebra I! This two-book bundle includes Algebra I For Dummies and Algebra I Workbook For Dummies. Together these two books give students helpful supplemental instruction and plenty of practice to help them score high in their high school Algebra class . . . this bundle is also for anyone looking to brush up on certain areas of Algebra. You might have a son, daughter, grandson, granddaughter, niece, nephew, or another special person in your life studying Algebra I who needs a little help. You want to help, but don't know mathematical formulas from ancient Egyptian hieroglyphs. Rest assured, you're in the right place. Algebra gives you a solid foundation to enable you to move on to more complicated subjects in mathematics. Algebra I For Dummies gently introduces you to Algebra I, starting with a review of the basics -- getting you comfortable with negative and positive numbers before wading into fractions, decimals, exponents, radicals, and in which order to complete operations. From there, you tackle prime numbers, distribution, and equations (linear and quadratic). Finally, you get to the answer of ... Unknown localization key: "more"

Objev podobné jako Algebra I For Dummies Book + Workbook Bundle - Mary Jane Sterling

This self-contained textbook, now in a thoroughly revised and expanded second edition, takes a matrix-oriented approach to Linear Algebra.

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Challenging and fun problems on every topic in a typical Algebra II course Algebra II: 1001 Practice Problems For Dummies gives you 1,001 opportunities to practice solving problems on all the major topics in Algebra II—in the book and online! Get extra help with tricky subjects, solidify what you’ve already learned, and get in-depth walk-throughs for every problem with this useful book. These practice problems and detailed answer explanations will get your advanced algebra juices flowing, no matter what your skill level. Thanks to Dummies, you have a resource to help you put key concepts into practice. Work through practice problems on all Algebra II topics covered in classStep through detailed solutions for every problem to build your understandingAccess practice questions online to study anywhere, any timeImprove your grade and up your study game with practice, practice, practiceThe material presented in Algebra II: 1001 Practice Problems For Dummies is an excellent resource for students, as well as parents and tutors looking to help supplement classroom instruction. Algebra II: 1001 Practice Problems For Dummies (9781119883562) was previously published as 1,001 Algebra II Practice Problems For Dummies (9781118446621). While this version features a new Dummies cover and design, the content is the ... Unknown localization key: "more"

Objev podobné jako Algebra II: 1001 Practice Problems For Dummies (+ Free Online Practice) - Mary Jane Sterling

For courses in Python programming. A clear and student-friendly introduction to Python Starting Out with Python® introduces programming concepts and problem-solving skills using Tony Gaddis'' accessible approach. Control structures are discussed before classes to familiarize new programmers with the fundamentals. Every chapter includes easy-to-read code listings, practical examples, and application exercises to help students gain confidence in their skills and learn to recognize the logic of developing high-quality programs. The 6th Edition is thoroughly updated with new language features and functionality for versions of Python up through Python 3.9. Hallmark features of this title Student-friendly presentation Written for novice programmers, Gaddis uses easy-to-understand language to introduce concepts. Control structures are explained, then classes and GUI applications. Optional turtle graphics sections are extremely effective at teaching the procedural steps of programming to beginners. Student-focused features Hundreds of example programs explore specific topics or more involved problem solving. Students can run the programs themselves using the source code. In the Spotlight case studies analyze how to solve a programming problem in step-by-step detail. Checkpoints and review questions let students test their understanding at regular intervals. Programming exercises offer hands-on practice opportunities at the end of each chapter. New and updated features of ... Unknown localization key: "more"

Objev podobné jako Starting Out with Python, Global Edition - Tony Gaddis

A 2-book bundle that adds up to success in basic math and pre-algebra People of all ages — from students in a math class to adults using math in the real world — often dislike ever having to use arithmetic, fractions, decimals, percentages, geometry, and so on. Math is all around us, but it doesn't have to be hard. Basic Math & Pre-Algebra For Dummies and Basic Math & Pre-Algebra Workbook For Dummies with Online Practice is a two-book bundle designed to help you improve your math skills whether you're a student tackling math homework or preparing for a test or an adult who wants to improve their own skills or help someone else learn to love numbers. Basic Math & Pre-Algebra For Dummies provides mathematical and algebraic concepts into easy-to-understand sections. You'll learn to: Master addition, subtraction, multiplication, and divisionWrangle the three E's of math: equations, expressions, and evaluationNever fear a word problem again (even ones with fractions, decimals, and percents)Know your prime numbers from composite numbersGet your mind around factors and multiplesLearn the parts of a fraction and how to add, subtract, multiply, and divide fractionsUnderstand scientific notation and how to use itDiscover the X in algebraAnd so ... Unknown localization key: "more"

Objev podobné jako Basic Math & Pre-Algebra For Dummies Book + Workbook Bundle - Mark Zegarelli

Designed for the introductory computing and computer science course, the student-friendly Computer Science Illuminated, Eighth Edition provides students with a solid foundation for further study, and offers non-majors a complete introduction to computing. Fully revised and updated, the eighth edition of this best-selling text retains the accessibility and in-depth coverage of previous editions, while incorporating all-new material on cutting-edge issues in computer science. Authored by the award-winning team Nell Dale and John Lewis, the text provides a unique and innovative layered approach, moving through the levels of computing from an organized, language-neutral perspective. Navigate Advantage for Computer Science Illuminated, Eighth Edition, is included with purchase and includes the following: the complete eBook, lab activities, supplemental programming chapters, animations, and additional Study Aids (Flash cards, Practice Quizzes, Learning Objectives, Lecture Outlines).

Objev podobné jako Computer Science Illuminated with Navigate Advantage Access - John Lewis, Nell Dale

Streamline Your Workflow and Boost Productivity with Python Automation In today's workplaces, there's a high demand for know-how on the Python programming language, especially for writing time-saving scripts that can simplify routine work tasks. Python Automation For Dummies delivers, with simple explanations of how you can use Python to automatically wrangle data files, manage media files, create shortcuts, find and organize web data, and even analyze social media for trends. With this easy-to-follow Dummies guide, you can upskill, expand your productivity, and speed up the process of generating data-driven insights. You'll even learn to enhance your Python automations with AI, for workflows that are faster and smarter. Review the basics of Python coding and follow steps for automating all sorts of tasksManage large file sets, organize and analyze data, and speed up research processesAutomate scheduling and other time-consuming tasks—and optimize work with AIFree up time and resources by automating routine work, so you can foucs on more important issues This is a great Dummies resource for Python developers interested in applying the popular coding language to make workflows more efficient.

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Python for Scientific Computing and Artificial Intelligence is split into 3 parts: in Section 1, the reader is introduced to the Python programming language and shown how Python can aid in the understanding of advanced High School Mathematics. In Section 2, the reader is shown how Python can be used to solve real-world problems from a broad range of scientific disciplines. Finally, in Section 3, the reader is introduced to neural networks and shown how TensorFlow (written in Python) can be used to solve a large array of problems in Artificial Intelligence (AI).This book was developed from a series of national and international workshops that the author has been delivering for over twenty years. The book is beginner friendly and has a strong practical emphasis on programming and computational modelling.Features:No prior experience of programming is requiredOnline GitHub repository available with codes for readers to practiceCovers applications and examples from biology, chemistry, computer science, data science, electrical and mechanical engineering, economics, mathematics, physics, statistics and binary oscillator computingFull solutions to exercises are available as Jupyter notebooks on the WebSupport MaterialGitHub Repository of Python Files and Notebooks: https://github.com/proflynch/CRC-Press/Solutions to All Exercises:Section 1: An Introduction to Python: https://drstephenlynch.github.io/webpages/Solutions_Section_1.htmlSection 2: Python for Scientific Computing: ... Unknown localization key: "more"

Objev podobné jako Python for Scientific Computing and Artificial Intelligence - Stephen Lynch

Doing Math with Python shows you how to use Python to delve into high school level math topics like statistics, geometry, probability, and calculus. You ll start with simple projects, like a factoring program and a quadratic-equation solver, and then create more complex projects once you ve gotten the hang of things. Along the way, you ll discover new ways to explore math and gain valuable programming skills that you ll use throughout your study of math and computer science. Learn how to: Describe your data with statistics, and visualize it with line graphs, bar charts, and scatter plots Explore set theory and probability with programs for coin flips, dicing, and other games of chance Solve algebra problems using Python s symbolic math functions Draw geometric shapes and explore fractals like the Barnsley fern, the Sierpinski triangle, and the Mandelbrot set Write programs to find derivatives and integrate functions Creative coding challenges and applied examples help you see how you can put your new math and coding skills into practice. You ll write an inequality solver, plot gravity s effect on how far a bullet will travel, shuffle a deck of cards, estimate the area of a circle by throwing ... Unknown localization key: "more"

Objev podobné jako Doing Math with Python - Amit Saha