introduction to machine learning with python andreas c mueller

Machine learning has become an integral part of many commercial applications and research projects, but this field is not exclusive to large companies with extensive research teams. If you use Python, even as a beginner, this book will teach you practical ways to build your own machine learning solutions.

Objev podobné jako Introduction to Machine Learning with Python - Andreas C. Mueller

This class-tested textbook will provide in-depth coverage of the fundamentals of machine learning, with an exploration of applications in information security. The book will cover malware detection, cryptography, and intrusion detection. The book will be relevant for students in machine learning and computer security courses.

Objev podobné jako Introduction to Machine Learning with Applications in Information Security - Mark Stamp

This book is a comprehensive guide suitable for beginners and experienced developers alike. It teaches readers how to master object-oriented programming (OOP) with Python and use it in real-world applications.Start by solidifying your OOP foundation with clear explanations of core concepts like use cases and class diagrams. This book goes beyond theory as you get practical examples with well-documented source code available in the book and on GitHub.This book doesn''t stop at the basics. Explore how OOP empowers fields like data persistence, graphical user interfaces (GUIs), machine learning, and data science, including social media analysis. Learn about machine learning algorithms for classification, regression, and unsupervised learning, putting you at the forefront of AI innovation.Each chapter is designed for hands-on learning. You''ll solidify your understanding with case studies, exercises, and projects that apply your newfound knowledge to real-world scenarios. The progressive structure ensures mastery, with each chapter building on the previous one, reinforced by exercises and projects.Numerous code examples and access to the source code enhance your learning experience. This book is your one-stop shop for mastering OOP with Python and venturing into the exciting world of machine learning and data science.

Objev podobné jako The Object-Oriented Approach to Problem Solving and Machine Learning with Python - Maha Hadid, Sujith Samuel Mathew, Shahbano Farooq, Mohammad Amin K

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A Concise Introduction to Machine Learning uses mathematics as the common language to explain a variety of machine learning concepts from basic principles and illustrates every concept using examples in both Python and MATLAB®, which are available on GitHub and can be run from there in Binder in a web browser. Each chapter concludes with exercises to explore the content.The emphasis of the book is on the question of Why—only if “why” an algorithm is successful is understood, can it be properly applied and the results trusted. Standard techniques are treated rigorously, including an introduction to the necessary probability theory. This book addresses the commonalities of methods, aims to give a thorough and in-depth treatment and develop intuition for the inner workings of algorithms, while remaining concise.This useful reference should be essential on the bookshelf of anyone employing machine learning techniques, since it is born out of strong experience in university teaching and research on algorithms, while remaining approachable and readable.

Objev podobné jako A Concise Introduction to Machine Learning - A.C. Faul

Introduction to Digital Music with Python Programming provides a foundation in music and code for the beginner. It shows how coding empowers new forms of creative expression while simplifying and automating many of the tedious aspects of production and composition.With the help of online, interactive examples, this book covers the fundamentals of rhythm, chord structure, and melodic composition alongside the basics of digital production. Each new concept is anchored in a real-world musical example that will have you making beats in a matter of minutes.Music is also a great way to learn core programming concepts such as loops, variables, lists, and functions, Introduction to Digital Music with Python Programming is designed for beginners of all backgrounds, including high school students, undergraduates, and aspiring professionals, and requires no previous experience with music or code.

Objev podobné jako Introduction to Digital Music with Python Programming - Cameron Roberts, Michael S. Horn, Melanie West

This practical guide provides more than 200 self-contained recipes to help you solve machine learning challenges you may encounter in your work.

Objev podobné jako Machine Learning with Python Cookbook - Chris Albon, Kyle Gallatin

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

The most human-friendly book on machine learning Somewhere buried in all the systems that drive artificial intelligence, you'll find machine learning—the process that allows technology to build knowledge based on data and patterns. Machine Learning For Dummies is an excellent starting point for anyone who wants deeper insight into how all this learning actually happens. This book offers an overview of machine learning and its most important practical applications. Then, you'll dive into the tools, code, and math that make machine learning go—and you'll even get step-by-step instructions for testing it out on your own. For an easy-to-follow introduction to building smart algorithms, this Dummies guide is your go-to. Piece together what machine learning is, what it can do, and what it can't doLearn the basics of machine learning code and how it integrates with large datasetsUnderstand the mathematical principles that AI uses to make itself smarterConsider real-world applications of machine learning and write your own algorithms With clear explanations and hands-on instruction, Machine Learning For Dummies is a great entry-level resource for developers looking to get started with AI and machine learning.

Objev podobné jako Machine Learning For Dummies - John Paul Mueller, Luca Massaron

This modern and self-contained book offers a clear and accessible introduction to the important topic of machine learning with neural networks. In addition to describing the mathematical principles of the topic, and its historical evolution, strong connections are drawn with underlying methods from statistical physics and current applications within science and engineering. Closely based around a well-established undergraduate course, this pedagogical text provides a solid understanding of the key aspects of modern machine learning with artificial neural networks, for students in physics, mathematics, and engineering. Numerous exercises expand and reinforce key concepts within the book and allow students to hone their programming skills. Frequent references to current research develop a detailed perspective on the state-of-the-art in machine learning research.

Objev podobné jako Machine Learning with Neural Networks - Bernhard Mehlig

This textbook is written for the first introductory course on scientific computing. It covers elementary numerical methods for linear systems, root finding, interpolation, numerical integration, numerical differentiation, least squares problems, initial value problems and boundary value problems. It includes short Matlab and Python tutorials to quickly get students started on programming. It makes the connection between elementary numerical methods with advanced topics such as machine learning and parallel computing.This textbook gives a comprehensive and in-depth treatment of elementary numerical methods. It balances the development, implementation, analysis and application of a fundamental numerical method by addressing the following questions.•Where is the method applied?•How is the method developed?•How is the method implemented?•How well does the method work?The material in the textbook is made as self-contained and easy-to-follow as possible with reviews and remarks. The writing is kept concise and precise. Examples, figures, paper-and-pen exercises and programming problems are deigned to reinforce understanding of numerical methods and problem-solving skills.

Objev podobné jako An Introduction to Scientific Computing with MATLAB® and Python Tutorials - Sheng Xu

This practical guide shows data scientists, data engineers, architects, and business analysts how to get started with a graph database using TigerGraph, one of the leading graph database models available.

Objev podobné jako Graph-Powered Analytics and Machine Learning with TigerGraph - Ph.D., Victor Lee, Xinyu Chang, Phuc Kien Nguyen

Introduction to Stochastic Finance with Market Examples, Second Edition presents an introduction to pricing and hedging in discrete and continuous-time financial models, emphasizing both analytical and probabilistic methods. It demonstrates both the power and limitations of mathematical models in finance, covering the basics of stochastic calculus for finance, and details the techniques required to model the time evolution of risky assets. The book discusses a wide range of classical topics including Black–Scholes pricing, American options, derivatives, term structure modeling, and change of numéraire. It also builds up to special topics, such as exotic options, stochastic volatility, and jump processes.New to this EditionNew chapters on Barrier Options, Lookback Options, Asian Options, Optimal Stopping Theorem, and Stochastic VolatilityContains over 235 exercises and 16 problems with complete solutions available online from the instructor resourcesAdded over 150 graphs and figures, for more than 250 in total, to optimize presentation57 R coding examples now integrated into the book for implementation of the methodsSubstantially class-tested, so ideal for course use or self-studyWith abundant exercises, problems with complete solutions, graphs and figures, and R coding examples, the book is primarily aimed at advanced undergraduate and graduate students in applied mathematics, financial engineering, and economics. It could be ... Unknown localization key: "more"

Objev podobné jako Introduction to Stochastic Finance with Market Examples - Nicolas Privault

A Concise Introduction to Robot Programming with ROS2 provides the reader with the concepts and tools necessary to bring a robot to life through programming. It will equip the reader with the skills necessary to undertake projects with ROS2, the new version of ROS. It is not necessary to have previous experience with ROS2 as it will describe its concepts, tools, and methodologies from the beginning.Key FeaturesUses the two programming languages officially supported in ROS2 (C++, mainly, and Python)Approaches ROS2 from three different but complementary dimensions: the Community, Computation Graph, and the WorkspaceIncludes a complete simulated robot, development and testing strategies, Behavior Trees, and Nav2 description, setup, and useA GitHub repository with code to assist readersIt will appeal to motivated engineering students, engineers, and professionals working with robot programming.

Objev podobné jako A Concise Introduction to Robot Programming with ROS 2 - Francisco Martin Rico

This best-selling book uses concrete examples, minimal theory, and production-ready Python frameworks--scikit-learn, Keras, and TensorFlow--to help you gain an intuitive understanding of the concepts and tools for building intelligent systems.

Objev podobné jako Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow 3e - Géron Aurélien

Discover a colorful, contemporary approach to traditional whitework with best-selling embroidery expert Trish Burr.Fresh and uplifting, Trish BurrÂ’s use of color brings a joyful lease of life to her stunning whitework designs.Complete with a comprehensive guide to getting started, and arranged in order of difficulty, this inspiring book contains 10 complete, brand-new projects, each with clear step-by-step instructions, an iron-on transfer, a full-size template and sumptuous photography.An expert teacher, and best-selling author, Trish has carefully constructed the book to appeal to beginners looking for a simple, no-nonsense approach to the technique, as well as more advanced embroiderers looking for inspiration.With subjects ranging from striking florals to birds, bees and butterflies, this book will inspire and delight with its variety of subjects. Contained within are:Re-usable iron-on transfers for all 10 designs, as well as full-size traceable templatesA comprehensive illustrated stitch library of all the stitches used throughoutA handy guide to selecting materials, preparing your fabric and using colorEasy-to-follow step-by-step instructions with plenty of inspiring photography

Objev podobné jako An Introduction to Whitework Embroidery with Colour - Trish Burr

If you love to sew, and want to share your joy of the craft with a young person, this book is for you!Kids can sew - this book shows you how! Step by step guides and 30 fun projects for kids 7 and up.Make 30 fun projects using your sewing machine!For age 7+, this practical sewing guide is jam-packed with great sewing ideas, clear diagrams and simple text to follow.Choose between projects for your bedroom, your wardrobe, your rucksack and more:BagsPincushionKeyringCushionEarphone caseScarfT-shirtPencil caseBeach towelOven gloves and moreWow your friends with your creations, then make gifts for them too.Girls and boys will love this introduction to machine sewing and the projects they can make and be proud of. Why let adults have all the fun? Let''s start machine sewing!

Objev podobné jako My First Sewing Machine - Coralie Bijasson

In just a few years, deep reinforcement learning (DRL) systems such as DeepMinds DQN have yielded remarkable results. This hybrid approach to machine learning shares many similarities with human learning: its unsupervised self-learning, self-discovery of strategies, usage of memory, balance of exploration and exploitation, and its exceptional flexibility. Exciting in its own right, DRL may presage even more remarkable advances in general artificial intelligence. Deep Reinforcement Learning in Python: A Hands-On Introduction is the fastest and most accessible way to get started with DRL. The authors teach through practical hands-on examples presented with their advanced OpenAI Lab framework. While providing a solid theoretical overview, they emphasize building intuition for the theory, rather than a deep mathematical treatment of results. Coverage includes: Components of an RL system, including environment and agents Value-based algorithms: SARSA, Q-learning and extensions, offline learning Policy-based algorithms: REINFORCE and extensions; comparisons with value-based techniques Combined methods: Actor-Critic and extensions; scalability through async methods Agent evaluation Advanced and experimental techniques, and more How to achieve breakthrough machine learning performance by combining deep neural networks with reinforcement learning Reduces the learning curve by relying on the authors’ OpenAI Lab framework: requires less upfront theory, math, and programming expertise Provides ... Unknown localization key: "more"

Objev podobné jako Foundations of Deep Reinforcement Learning - Laura Graesser, Wah Loon Keng

Learning and Behavior reviews how people and animals learn and how their behaviors are changed because of learning. It describes the most important principles, theories, controversies, and experiments that pertain to learning and behavior that are applicable to diverse species and different learning situations. Both classic studies and recent trends and developments are explored, providing a comprehensive survey of the field. Although the behavioral approach is emphasized, many cognitive theories are covered as well, along with a chapter on comparative cognition. Real-world examples and analogies make the concepts and theories more concrete and relevant to students. In addition, most chapters provide examples of how the principles covered have been employed in applied and clinical behavior analysis. The text proceeds from the simple to the complex. The initial chapters introduce the behavioral, cognitive, and neurophysiological approaches to learning. Later chapters give extensive coverage of classical conditioning and operant conditioning, beginning with basic concepts and findings and moving to theoretical questions and current issues. Other chapters examine the topics of reinforcement schedules, avoidance and punishment, stimulus control and concept learning, observational learning and motor skills, comparative cognition, and choice. Thoroughly updated, each chapter features many new studies and references that reflect recent ... Unknown localization key: "more"

Objev podobné jako Learning and Behavior - Amy L. Odum, James E. Mazur

Help children learn to MACHINE SEW with 30 SUPER-FUN and CREATIVE projects!An all-new collection from BESTSELLING author ANGELA PRESSLEY, expert sewing teacher and star of SEWING STREET TV. Packed full of colorful and unique ideas, this STEP-BY-STEP guide will inspire children to machine-sew their own amazing toys, accessories, decorations, and gifts. Angela Pressley has designed 30 projects she knows kids will love to make, from cuddly mama and baby stringray toys to a cute sausage dog complete with a mini bandana. Customize bedrooms with a colorful striped pillow and wall storage pockets and make unique, on-trend accessories including a bubble tea pencil case and a matching slouchy beanie and mittens. Also included are easy-to-use templates, a guide to the basic sewing kit needed and a handy techniques section with clear step-by-step illustrations. Each of the projects has a skill rating, so children can start with the simplest designs and move on to more challenging projects as they build their skills and confidence.

Objev podobné jako Sewing Machine Projects for Children - Angela Pressley

Make a difference to classroom learning with this textbook, written for the CACHE qualification by highly respected and experienced author Louise Burnham.-Develop your skills as a teaching assistant with coverage of all units in the new CACHE qualification. -Build confidence in your role with practical advice and full explanations from best-selling author Louise Burnham. -Translate theory into practice with Tips for Best Practice and Case Studies for challenging topics such as Behaviour Management.-Strengthen your understanding of theory and practice, with comprehensive information linked clearly to assessment criteria.-Find all the information you need with the colourful, clear design, and appropriate language throughout. -Make the most of your training with the Stretch and Challenge feature.-Engage in debate on important topics with Classroom Discussion suggestions.

Objev podobné jako NCFE CACHE Level 3 Diploma in Supporting Teaching and Learning - Louise Burnham

This print textbook is available for students to rent for their classes. The Pearson print rental program provides students with affordable access to learning materials, so they come to class ready to succeed. For courses in computer programming . A user-friendly, code-intensive introduction to C programming with case studies introducing applications and system programming C How to Program is a comprehensive introduction to programming in C. Like other texts of the Deitels’ How to Program series, the book’s modular presentation serves as a detailed beginner source of information for college students looking to embark on a career in coding, or instructors and software-development professionals seeking to learn how to program with C. The signature Deitel live-code approach presents concepts in the context of 142 full-working programs rather than incomplete snips of code. This gives students a chance to run each program as they study it and see how their learning applies to real-world programming scenarios Current standards, contemporary practice, and hands-on learning opportunities are integrated throughout the 9th Edition. Over 340 new integrated Self-Check exercises with answers allow students to test their understanding of important concepts — and check their code — as they read. New and enhanced case studies ... Unknown localization key: "more"

Objev podobné jako C How to Program: With Case Studies in Applications and SystemsProgramming, Global Edition - Harvey Deitel, Paul Deitel

Official preparation for the 'IELTS Life Skills' Speaking and Listening exam This Student's Book prepares candidates for the IELTS Life Skills - B1 Speaking and Listening exam which is used to prove language level for UK Visa requirements. It includes four practice tests for the exam with a full answer key. There is an introduction to the exam with information about what to expect and guidelines for teachers on how to assess students. There are model Speaking answers, practice exercises and exam tips to support candidates. The accompanying Audio is downloadable using an access code in the book. Audio CDs are also available separately for class use.

Objev podobné jako IELTS Life Skills Official Cambridge Test Practice B1 Student´s Book with Answers and Audio - Anthony Cosgrove

Official preparation for the 'IELTS Life Skills' Speaking and Listening exam This Student's Book prepares candidates for the IELTS Life Skills - A1 Speaking and Listening exam which is used to prove language level for UK Visa requirements. It includes four practice tests for the exam with a full answer key. There is an introduction to the exam with information about what to expect and guidelines for teachers on how to assess students. There are model Speaking answers, practice exercises and exam tips to support candidates. The accompanying Audio is downloadable using an access code in the book. Audio CDs are also available separately for class use.

Objev podobné jako IELTS Life Skills Official Cambridge Test Practice A1 Student´s Book with Answers and Audio - Mary Matthews

A fun, informative and practical introduction to safely foraging with kids, from the UK's bestselling foraging author.

Objev podobné jako Foraging with Kids - Nozedar Adele

Juno, the Big Brown Dog, is worried because her sister Juniper is unwell and must travel to London to visit a specialist vet who, hopefully, can make her better. Whilst on this trip, Juno learns that not only dogs get ill, but our environment can become unhealthy. This can cause serious harm to dogs, humans, other animals and their habitats. She also discovers that there are various measures we can take to reverse some of this damage. This beautifully illustrated story of Juno’s adventures in London will help children understand the reality and urgency of The Climate Crisis. All proceeds from this book will be given to animal welfare charities – Duo Ibiza, All Dogs Matter and Dogs Trust.Sales Points:Written to inspire conversations about the greatest challenge of our time – The Climate CrisisContains a short introduction to this crisis with a focus on energy production, explaining some of the solutionsFull-colour illustrations help explain complex themes in approachable and positive waysSecond book about the lovable, intelligent dog JunoAll profit from this book to animal welfare charities – Duo Ibiza, All Dogs Matter and Dog’s Trust

Objev podobné jako Juno Goes to London - Jim Mellon

A compendium of Wiccan knowledge, ideal for the novice witchThe Beginner’s Guide to Wicca is the essential companion for anyone new to the ancient practice of magic. Kirsten Riddle provides a friendly, straightforward introduction to witchcraft, filled with practical tips for incorporating the Wiccan way into every aspect of your daily life. Kirsten dispels common misconceptions, explains the peaceful ethos of this nature-based spiritual practice, and provides a quick and easy quiz that allows you to discover your Wiccan strengths. Chapters cover topics such as herbal, moon, and kitchen magic, and include simple spells and rituals using everyday objects and household items. Kirsten’s easy-to-follow, modern spells can be used to boost your creativity, improve your health, and revive your love life. With The Beginner’s Guide to Wicca you will discover how to tap into the powerful energy of the natural world and take your first steps on the Wiccan path.

Objev podobné jako The Beginner’s Guide to Wicca - Kirsten Riddle

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

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

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

 "A well-constructed and concisely written book, incorporating a balanced combination of textual explanations and well-presented mathematical descriptions, which serves both as an introduction to many important aspects of radar but also as an extensive exercise in the usage and application of both the MATLAB and Python programming applications. It is eminently readable and understandable. I assess that it is probably most relevant to post graduate student scientists and engineers requiring a moderately detailed understanding of aspects of radar with a view to practical applications”Aerospace Magazine This comprehensive resource provides readers with the tools necessary to perform analysis of various waveforms for use in radar systems. It provides information about how to produce synthetic aperture (SAR) images by giving a tomographic formulation and implementation for SAR imaging. Tracking filter fundamentals, and each parameter associated with the filter and how each affects tracking performance are also presented. Various radar cross section measurement techniques are covered, along with waveform selection analysis through the study of the ambiguity function for each particular waveform from simple linear frequency modulation (LFM) waveforms to more complicated coded waveforms.  The text includes the Python tool suite, which allows the reader to analyze and predict radar performance ... Unknown localization key: "more"

Objev podobné jako Introduction to Radar Using Python and MATLAB - Lee Andrew Harrison

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

The new edition of an introduction to the art of computational problem solving using Python.This book introduces students with little or no prior programming experience to the art of computational problem solving using Python and various Python libraries, including numpy, matplotlib, random, pandas, and sklearn. It provides students with skills that will enable them to make productive use of computational techniques, including some of the tools and techniques of data science for using computation to model and interpret data as well as substantial material on machine learning. All of the code in the book and an errata sheet are available on the book’s web page on the MIT Press website.

Objev podobné jako Introduction to Computation and Programming Using Python, third edition - John V. Guttag

It''s time to dispel the myth that machine learning is difficult. Grokking Machine Learning teaches you how to apply ML to your projects using only standard Python code and high school-level math. No specialist knowledge is required to tackle the hands-on exercises using readily available machine learning tools! In Grokking Machine Learning, expert machine learning engineer Luis Serrano introduces the most valuable ML techniques and teaches you how to make them work for you. Practical examples illustrate each new concept to ensure you’re grokking as you go. You’ll build models for spam detection, language analysis, and image recognition as you lock in each carefully-selected skill. Packed with easy-to-follow Python-based exercises and mini-projects, this book sets you on the path to becoming a machine learning expert. Key Features · Different types of machine learning, including supervised and unsupervised learning · Algorithms for simplifying, classifying, and splitting data · Machine learning packages and tools · Hands-on exercises with fully-explained Python code samples For readers with intermediate programming knowledge in Python or a similar language. About the technology Machine learning is a collection of mathematically-based techniques and algorithms that enable computers to identify patterns and generate predictions from data. This revolutionary data analysis ... Unknown localization key: "more"

Objev podobné jako Grokking Machine Learning - Luis Serrano

Stable Diffusion, ChatGPT, Whisper - these are just a few examples of incredible applications powered by developments in machine learning. Despite the ubiquity of machine learning applications running in production, there are only a few viable language choices for data science and machine learning tasks. Elixir''s Nx project seeks to change that. With Nx, you can leverage the power of machine learning in your applications, using the battle-tested Erlang VM in a pragmatic language like Elixir. In this book, you''ll learn how to leverage Elixir and the Nx ecosystem to solve real-world problems in computer vision, natural language processing, and more.The Elixir Nx project aims to make machine learning possible without the need to leave Elixir for solutions in other languages. And even if concepts like linear models and logistic regression are new to you, you''ll be using them and much more to solve real-world problems in no time.Start with the basics of the Nx programming paradigm - how it differs from the Elixir programming style you''re used to and how it enables you to write machine learning algorithms. Use your understanding of this paradigm to implement foundational machine learning algorithms from scratch. Go deeper and discover the power of ... Unknown localization key: "more"

Objev podobné jako Machine Learning in Elixir - Sean Moriarity

Machine Learning is an integral tool in a business analyst’s arsenal because the rate at which data is being generated from different sources is increasing and working on complex unstructured data is becoming inevitable. Data collection, data cleaning, and data mining are rapidly becoming more difficult to analyze than just importing information from a primary or secondary source. The machine learning model plays a crucial role in predicting the future performance and results of a company. In real-time, data collection and data wrangling are the important steps in deploying the models. Analytics is a tool for visualizing and steering data and statistics. Business analysts can work with different datasets -- choosing an appropriate machine learning model results in accurate analyzing, forecasting the future, and making informed decisions. The global machine learning market was valued at $1.58 billion in 2017 and is expected to reach $20.83 billion in 2024 -- growing at a CAGR of 44.06% between 2017 and 2024. The authors have compiled important knowledge on machine learning real-time applications in business analytics. This book enables readers to get broad knowledge in the field of machine learning models and to carry out their future research work. The future trends of ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Business Analytics

MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning —also known as data mining or data analytics— is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This is the second R edition of Machine Learning for Business Analytics. This edition also includes: A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using RAn expanded chapter focused on discussion of deep learning techniquesA new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter devoted ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Business Analytics - Peter Gedeck, Galit Shmueli, Peter C. Bruce, Nitin R. Patel, Inbal Yahav

Machine learning can help managers make better predictions, automate complex tasks and improve business operations. Managers who are familiar with machine learning are better placed to navigate the increasingly digital world we live in. There is a view that machine learning is a highly technical subject that can only be understood by specialists. However, many of the ideas that underpin machine learning are straightforward and accessible to anyone with a bit of curiosity. This book is for managers who want to understand what machine learning is about, but who lack a technical background in computer science, statistics or math. The book describes in plain language what machine learning is and how it works. In addition, it explains how to manage machine learning projects within an organization. This book should appeal to anyone that wants to learn more about using machine learning to drive value in real-world organizations.

Objev podobné jako Machine Learning for Managers - Paul Geertsema

With an evolutionary advancement of Machine Learning (ML) algorithms, a rapid increase of data volumes and a significant improvement of computation powers, machine learning becomes hot in different applications. However, because of the nature of "black-box" in ML methods, ML still needs to be interpreted to link human and machine learning for transparency and user acceptance of delivered solutions. This edited book addresses such links from the perspectives of visualisation, explanation, trustworthiness and transparency. The book establishes the link between human and machine learning by exploring transparency in machine learning, visual explanation of ML processes, algorithmic explanation of ML models, human cognitive responses in ML-based decision making, human evaluation of machine learning and domain knowledge in transparent ML applications.This is the first book of its kind to systematically understand the current active research activities and outcomes related to human and machine learning. The book will not only inspire researchers to passionately develop new algorithms incorporating human for human-centred ML algorithms, resulting in the overall advancement of ML, but also help ML practitioners proactively use ML outputs for informative and trustworthy decision making.This book is intended for researchers and practitioners involved with machine learning and its applications. The book will especially ... Unknown localization key: "more"

Objev podobné jako Human and Machine Learning

MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning—also known as data mining or predictive analytics—is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications with Analytic Solver® Data Mining provides a comprehensive introduction and an overview of this methodology. The fourth edition of this best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, time series forecasting and network analytics. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques. This fourth edition of Machine Learning for Business Analytics also includes: An expanded chapter on deep learningA new chapter on experimental feedback techniques, including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniquesEnd-of-chapter ... Unknown localization key: "more"

Objev podobné jako Machine Learning for Business Analytics - Galit Shmueli, Peter C. Bruce, Nitin R. Patel, Kuber R. Deokar

Develop a mathematical intuition around machine learning algorithms to improve model performance and effectively troubleshoot complex ML problems. For intermediate machine learning practitioners familiar with linear algebra, probability, and basic calculus. Machine Learning Algorithms in Depth dives into the design and underlying principles of some of the most exciting machine learning (ML) algorithms in the world today. With a particular emphasis on probability-based algorithms, you will learn the fundamentals of Bayesian inference and deep learning. You will also explore the core data structures and algorithmic paradigms for machine learning. You will explore practical implementations of dozens of ML algorithms, including: Monte Carlo Stock Price Simulation Image Denoising using Mean-Field Variational Inference EM algorithm for Hidden Markov Models Imbalanced Learning, Active Learning and Ensemble Learning Bayesian Optimisation for Hyperparameter Tuning Dirichlet Process K-Means for Clustering Applications Stock Clusters based on Inverse Covariance Estimation Energy Minimisation using Simulated Annealing Image Search based on ResNet Convolutional Neural Network Anomaly Detection in Time-Series using Variational Autoencoders Each algorithm is fully explored with both math and practical implementations so you can see how they work and put into action. About the technology Fully understanding how machine learning algorithms function is essential for any serious ML ... Unknown localization key: "more"

Objev podobné jako Machine Learning Algorithms in Depth - Vadim Smolyakov

A practical and innovative textbook detailing how to build real-world software products with machine learning components, not just models.Traditional machine learning texts focus on how to train and evaluate the machine learning model, while MLOps books focus on how to streamline model development and deployment. But neither focus on how to build actual products that deliver value to users. This practical textbook, by contrast, details how to responsibly build products with machine learning components, covering the entire development lifecycle from requirements and design to quality assurance and operations. Machine Learning in Production brings an engineering mindset to the challenge of building systems that are usable, reliable, scalable, and safe within the context of real-world conditions of uncertainty, incomplete information, and resource constraints. Based on the author’s popular class at Carnegie Mellon, this pioneering book integrates foundational knowledge in software engineering and machine learning to provide the holistic view needed to create not only prototype models but production-ready systems. •   Integrates coverage of cutting-edge research, existing tools, and real-world applications•   Provides students and professionals with an engineering view for production-ready machine learning systems•   Proven in the classroom•   Offers supplemental resources including slides, videos, ... Unknown localization key: "more"

Objev podobné jako Machine Learning in Production - Christian Kastner

The book provides an accessible, comprehensive introduction for beginners to machine learning, equipping them with the fundamental skills and techniques essential for this field.It enables beginners to construct practical, real-world solutions powered by machine learning across diverse application domains. It demonstrates the fundamental techniques involved in data collection, integration, cleansing, transformation, development, and deployment of machine learning models. This book emphasizes the importance of integrating responsible and explainable AI into machine learning models, ensuring these principles are prioritized rather than treated as an afterthought. To support learning, this book also offers information on accessing additional machine learning resources such as datasets, libraries, pre-trained models, and tools for tracking machine learning models.This is a core resource for students and instructors of machine learning and data science looking for beginner-friendly material which offers real-world applications and takes ethical discussions into account.

Objev podobné jako Practical Machine Learning - Ally S. Nyamawe, Salim A. Diwani, Noe E. Nnko, Mohamedi M. Mjahidi, Kulwa Malyango, Godbless G. Minja

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

An advanced book for researchers and graduate students working in machine learning and statistics who want to learn about deep learning, Bayesian inference, generative models, and decision making under uncertainty.An advanced counterpart to Probabilistic Machine Learning: An Introduction, this high-level textbook provides researchers and graduate students detailed coverage of cutting-edge topics in machine learning, including deep generative modeling, graphical models, Bayesian inference, reinforcement learning, and causality. This volume puts deep learning into a larger statistical context and unifies approaches based on deep learning with ones based on probabilistic modeling and inference. With contributions from top scientists and domain experts from places such as Google, DeepMind, Amazon, Purdue University, NYU, and the University of Washington, this rigorous book is essential to understanding the vital issues in machine learning.Covers generation of high dimensional outputs, such as images, text, and graphs Discusses methods for discovering insights about data, based on latent variable models Considers training and testing under different distributionsExplores how to use probabilistic models and inference for causal inference and decision makingFeatures online Python code accompanimentÂ

Objev podobné jako Probabilistic Machine Learning - Kevin P. Murphy

This textbook is an introductory guide to applied machine learning, specifically for biology students. It familiarizes biology students with the basics of modern computer science and mathematics and emphasizes the real-world applications of these subjects. The chapters give an overview of computer systems and programming languages to establish a basic understanding of the important concepts in computer systems. Readers are introduced to machine learning and artificial intelligence in the field of bioinformatics, connecting these applications to systems biology, biological data analysis and predictions, and healthcare diagnosis and treatment. This book offers a necessary foundation for more advanced computer-based technologies used in biology, employing case studies, real-world issues, and various examples to guide the reader from the basic prerequisites to machine learning and its applications.

Objev podobné jako A Guide to Applied Machine Learning for Biologists

Many machine learning problems are too complex to be resolved by a single model or algorithm. Ensemble machine learning trains a group of diverse machine learning models to work together to solve a problem. By aggregating their output, these ensemble models can flexibly deliver rich and accurate results. Ensemble Methods for Machine Learning is a guide to ensemble methods with proven records in data science competitions and real world applications. Learning from hands-on case studies, you''ll develop an under-the-hood understanding of foundational ensemble learning algorithms to deliver accurate, performant models. About the Technology Ensemble machine learning lets you make robust predictions without needing the huge datasets and processing power demanded by deep learning. It sets multiple models to work on solving a problem, combining their results for better performance than a single model working alone. This "wisdom of crowds" approach distils information from several models into a set of highly accurate results.

Objev podobné jako Ensemble Methods for Machine Learning - Gautam Kunapuli

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every chapter includes worked examples and exercises to test understanding. Programming tutorials are offered on the book''s web site.

Objev podobné jako Mathematics for Machine Learning - A. Aldo Faisal, Marc Peter Deisenroth, Cheng Soon Ong

A Proven, Hands-On Approach for Students without a Strong Statistical FoundationSince the best-selling first edition was published, there have been several prominent developments in the field of machine learning, including the increasing work on the statistical interpretations of machine learning algorithms. Unfortunately, computer science students without a strong statistical background often find it hard to get started in this area. Remedying this deficiency, Machine Learning: An Algorithmic Perspective, Second Edition helps students understand the algorithms of machine learning. It puts them on a path toward mastering the relevant mathematics and statistics as well as the necessary programming and experimentation.New to the Second EditionTwo new chapters on deep belief networks and Gaussian processes Reorganization of the chapters to make a more natural flow of contentRevision of the support vector machine material, including a simple implementation for experimentsNew material on random forests, the perceptron convergence theorem, accuracy methods, and conjugate gradient optimization for the multi-layer perceptronAdditional discussions of the Kalman and particle filtersImproved code, including better use of naming conventions in PythonSuitable for both an introductory one-semester course and more advanced courses, the text strongly encourages students to practice with the code. Each chapter includes detailed examples along with further reading and ... Unknown localization key: "more"

Objev podobné jako Machine Learning - Stephen Marsland

Multivariate Statistics and Machine Learning is a hands-on textbook providing an in-depth guide to multivariate statistics and select machine learning topics using R and Python software.The book offers a theoretical orientation to the concepts required to introduce or review statistical and machine learning topics, and in addition to teaching the techniques, instructs readers on how to perform, implement, and interpret code and analyses in R and Python in multivariate, data science, and machine learning domains. For readers wishing for additional theory, numerous references throughout the textbook are provided where deeper and less “hands on” works can be pursued. With its unique breadth of topics covering a wide range of modern quantitative techniques, user-friendliness and quality of expository writing, Multivariate Statistics and Machine Learning will serve as a key and unifying introductory textbook for students in the social, natural, statistical and computational sciences for years to come.  Â

Objev podobné jako Multivariate Statistics and Machine Learning - Daniel J. Denis

Learn to code like a professional with Python – an open source, versatile, and powerful programming languageKey FeaturesLearn the fundamentals of programming with Python – one of the best languages ever createdDevelop a strong set of programming skills that you will be able to express in any situation, on every platform, thanks to Python’s portabilityCreate outstanding applications of all kind, from websites to scripting, and from GUIs to data scienceBook DescriptionLearning Python has a dynamic and varied nature. It reads easily and lays a good foundation for those who are interested in digging deeper. It has a practical and example-oriented approach through which both the introductory and the advanced topics are explained. Starting with the fundamentals of programming and Python, it ends by exploring very different topics, like GUIs, web apps and data science. The book takes you all the way to creating a fully fledged application. The book begins by exploring the essentials of programming, data structures and teaches you how to manipulate them. It then moves on to controlling the flow of a program and writing reusable and error proof code. You will then explore different programming paradigms that will allow you to find the best approach to ... Unknown localization key: "more"

Objev podobné jako Learning Python - Fabrizio Romano