Machine Learning For Dummies

Machine Learning For Dummies Author John Paul Mueller
ISBN-10 9781119245773
Release 2016-05-11
Pages 432
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Your no-nonsense guide to making sense of machine learning Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how invaluable it is. Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks. Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data—or anything in between—this guide makes it easier to understand and implement machine learning seamlessly. Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!



Machine Learning

Machine Learning Author Ethem Alpaydin
ISBN-10 9780262529518
Release 2016-10-07
Pages 224
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A concise overview of machine learning -- computer programs that learn from data -- which underlies applications that include recommendation systems, face recognition, and driverless cars.



Android Apps for Absolute Beginners

Android Apps for Absolute Beginners Author Wallace Jackson
ISBN-10 9781484222683
Release 2017-03-14
Pages 484
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Get your first Android apps up and running with the help of plain English and practical examples. If you have a great idea for an Android app, but have never programmed before, then this book is for you. Android Apps for Absolute Beginners cuts through the fog of jargon and mystery that surrounds Android app development, and gives you simple, step-by-step instructions to get you started. This book teaches Android application development in language anyone can understand, giving you the best possible start in Android development. It provides clean, straightforward examples that make learning easy, allowing you to pick up the concepts without fuss. It offers clear code descriptions and layout so that you can get your apps running as soon as possible Although this book covers what's new in Android 7, it is also backwards compatible to cover some of the previous Android releases. What You'll Learn Download, install, and configure the latest software needed for Android app development Work efficiently using an integrated development environment (IDE) Build useful, attractive applications and get them working immediately Create apps with ease using XML markup and drag-and-drop graphical layout editors Use new media and graphics to skin your app so that it has maximum appeal Create advanced apps combining XML, Java and new media content Who This Book Is For If you have a great idea for an Android app, but have never programmed before, then this book is for you. You don’t need to have any previous computer programming skills — as long as you have a desire to learn and you know which end of the mouse is which, the world of Android apps development awaits.



Machine Learning with R

Machine Learning with R Author Brett Lantz
ISBN-10 9781782162155
Release 2013-10-25
Pages 396
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Written as a tutorial to explore and understand the power of R for machine learning. This practical guide that covers all of the need to know topics in a very systematic way. For each machine learning approach, each step in the process is detailed, from preparing the data for analysis to evaluating the results. These steps will build the knowledge you need to apply them to your own data science tasks.Intended for those who want to learn how to use R's machine learning capabilities and gain insight from your data. Perhaps you already know a bit about machine learning, but have never used R; or perhaps you know a little R but are new to machine learning. In either case, this book will get you up and running quickly. It would be helpful to have a bit of familiarity with basic programming concepts, but no prior experience is required.



Fundamentals of Machine Learning for Predictive Data Analytics

Fundamentals of Machine Learning for Predictive Data Analytics Author John D. Kelleher
ISBN-10 9780262029445
Release 2015-07-24
Pages 624
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A comprehensive introduction to the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications.



Artificial Intelligence with Python

Artificial Intelligence with Python Author Prateek Joshi
ISBN-10 178646439X
Release 2017-04-28
Pages 521
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Build real-world AI applications with Python to intelligently interact with your surroundingsAbout This Book* Step into the amazing world of intelligent apps using this comprehensive guide* Enter the world of AI, explore it, and become independent to create your own AI apps* Work through simple yet insightful examples that will get you up and running with artificial intelligence in no timeWho This Book Is ForThis book is for Python developers who want to build real-world AI applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to implement AI techniques in their existing technology stacks.What You Will Learn* Find out how to use different classification and regression techniques* Understand the concept of clustering and how to use it to automatically segment data* See how to build an intelligent recommender system* Understand logic programming and how to use it* Develop automatic speech recognition systems* Understand the basics of heuristic search and genetic programming* Develop an understanding of reinforcement learning* Discover how to build AI applications centered on images, text, and time series data* Understand how to use deep learning algorithms and build applications based on itIn DetailAI is becoming increasingly relevant in the modern world where the ecosystem is driven by technology and data. AI is used extensively across many fields such as robotics, computer vision, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various AI algorithms that can be used to build various applications.During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of the AI concepts, you will learn how to develop the various building blocks of AI using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application based on images, text, stock market, or some other form of data, this exciting book on AI will definitely guide you all the way!



Hands On Machine Learning with Scikit Learn and TensorFlow

Hands On Machine Learning with Scikit Learn and TensorFlow Author Aurélien Géron
ISBN-10 1491962291
Release 2017-04
Pages 566
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Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—scikit-learn and TensorFlow—author Aur�lien G�ron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use scikit-learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets Apply practical code examples without acquiring excessive machine learning theory or algorithm details



Python Machine Learning

Python Machine Learning Author Sebastian Raschka
ISBN-10 9781783555147
Release 2015-09-23
Pages 454
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Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn effective strategies and best practices to improve and optimize machine learning systems and algorithms Ask – and answer – tough questions of your data with robust statistical models, built for a range of datasets Who This Book Is For If you want to find out how to use Python to start answering critical questions of your data, pick up Python Machine Learning – whether you want to get started from scratch or want to extend your data science knowledge, this is an essential and unmissable resource. What You Will Learn Explore how to use different machine learning models to ask different questions of your data Learn how to build neural networks using Keras and Theano Find out how to write clean and elegant Python code that will optimize the strength of your algorithms Discover how to embed your machine learning model in a web application for increased accessibility Predict continuous target outcomes using regression analysis Uncover hidden patterns and structures in data with clustering Organize data using effective pre-processing techniques Get to grips with sentiment analysis to delve deeper into textual and social media data In Detail Machine learning and predictive analytics are transforming the way businesses and other organizations operate. Being able to understand trends and patterns in complex data is critical to success, becoming one of the key strategies for unlocking growth in a challenging contemporary marketplace. Python can help you deliver key insights into your data – its unique capabilities as a language let you build sophisticated algorithms and statistical models that can reveal new perspectives and answer key questions that are vital for success. Python Machine Learning gives you access to the world of predictive analytics and demonstrates why Python is one of the world's leading data science languages. If you want to ask better questions of data, or need to improve and extend the capabilities of your machine learning systems, this practical data science book is invaluable. Covering a wide range of powerful Python libraries, including scikit-learn, Theano, and Keras, and featuring guidance and tips on everything from sentiment analysis to neural networks, you'll soon be able to answer some of the most important questions facing you and your organization. Style and approach Python Machine Learning connects the fundamental theoretical principles behind machine learning to their practical application in a way that focuses you on asking and answering the right questions. It walks you through the key elements of Python and its powerful machine learning libraries, while demonstrating how to get to grips with a range of statistical models.



Grokking Deep Learning

Grokking Deep Learning Author Andrew Trask
ISBN-10 1617293709
Release 2017-03-31
Pages 325
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Artificial Intelligence is the most exciting technology of the century, and Deep Learning is, quite literally, the "brain" behind the world's smartest Artificial Intelligence systems out there. Grokking Deep Learning is the perfect place to begin the deep learning journey. Rather than just learning the "black box" API of some library or framework, readers will actually understand how to build these algorithms completely from scratch. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.



Python for Kids

Python for Kids Author Jason R. Briggs
ISBN-10 9781593274078
Release 2013
Pages 344
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Introduces the basics of the Python programming language, covering how to use data structures, organize and reuse code, draw shapes and patterns with turtle, and create games and animations with tkinter.



Adventures in Arduino

Adventures in Arduino Author Becky Stewart
ISBN-10 9781118948460
Release 2015-04-14
Pages 320
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Arduino programming for the absolute beginner, with project-based learning Adventures in Arduino is the beginner's guide to Arduino programming, designed specifically for 11-to 15-year olds who want to learn about Arduino, but don't know where to begin. Starting with the most basic concepts, this book coaches you through nine great projects that gradually build your skills as you experiment with electronics. The easy-to-follow design and clear, plain-English instructions make this book the ideal guide for the absolute beginner, geared toward those with no computing experience. Each chapter includes a video illuminating the material, giving you plenty of support on your journey to electronics programming. Arduino is a cheap, readily available hardware development platform based around an open source, programmable circuit board. Combining these chips with sensors and servos allows you to gain experience with prototyping as you build interactive electronic crafts to bring together data and even eTextiles. Adventures in Arduino gets you started on the path of scientists, programmers, and engineers, showing you the fun way to learn electronic programming and interaction design. Discover how and where to begin Arduino programming Develop the skills and confidence to tackle other projects Make the most of Arduino with basic programming concepts Work with hardware and software to create interactive electronic devices There's nothing like watching your design come to life and interact with the real world, and Arduino gives you the capability to do that time and again. The right knowledge combined with the right tools can create an unstoppable force of innovation, and your curiosity is the spark that ignites the flame. Adventures in Arduino gets you started on the right foot, but the path is totally up to you.



Computer Science Distilled

Computer Science Distilled Author Wladston Ferreira Filho
ISBN-10 0997316004
Release 2017-01-01
Pages 170
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Computer Science Distilled has been writing in one form or another for most of life. You can find so many inspiration from Computer Science Distilled also informative, and entertaining. Click DOWNLOAD or Read Online button to get full Computer Science Distilled book for free.



Introduction to Machine Learning

Introduction to Machine Learning Author Ethem Alpaydin
ISBN-10 9780262028189
Release 2014-08-29
Pages 640
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The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. Subjects include supervised learning; Bayesian decision theory; parametric, semi-parametric, and nonparametric methods; multivariate analysis; hidden Markov models; reinforcement learning; kernel machines; graphical models; Bayesian estimation; and statistical testing.Machine learning is rapidly becoming a skill that computer science students must master before graduation. The third edition of Introduction to Machine Learning reflects this shift, with added support for beginners, including selected solutions for exercises and additional example data sets (with code available online). Other substantial changes include discussions of outlier detection; ranking algorithms for perceptrons and support vector machines; matrix decomposition and spectral methods; distance estimation; new kernel algorithms; deep learning in multilayered perceptrons; and the nonparametric approach to Bayesian methods. All learning algorithms are explained so that students can easily move from the equations in the book to a computer program. The book can be used by both advanced undergraduates and graduate students. It will also be of interest to professionals who are concerned with the application of machine learning methods.



Python Programming for Biology

Python Programming for Biology Author Tim J. Stevens
ISBN-10 9780521895835
Release 2015-02-12
Pages 711
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This book introduces Python as a powerful tool for the investigation of problems in computational biology, for novices and experienced programmers alike.



Computers For Seniors For Dummies

Computers For Seniors For Dummies Author Nancy C. Muir
ISBN-10 9781119049548
Release 2015-09-22
Pages 384
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The bestselling guide that helps the mature choose a computer and get online for shopping, paying bills, staying in touch with family and friends, and much more! A first computer can be confusing and intimidating at any age. Luckily, Computers For Seniors For Dummies is here to help the over-55 crowd conquer the uncertainty and fear with clear-cut, easy-to-understand steps on how to get the most out of your new computer. Inside, you'll find step-by-step guidance on getting started, from turning the computer on and using the keyboard and mouse to finding your way around the new Windows 9 operating system. In no time, you'll confidently navigate your way around your new computer to email with family and friends, stay connected on social media, shop securely online, research topics of interest, find recipes and diet tips, and so much more. The computer has become a household and business mainstay and continues to change the way people communicate, work, shop, invest, and spend their free time. Whether you're looking to use a computer for bookkeeping, making travel pans, socializing, shopping, or just plain fun, this clear and friendly guide takes the intimidation out of computer basics and the ever-evolving technology that surrounds it. Large-print format and drawings make it easy to read and understand Includes chapter openers that present the tasks covered with associated page numbers to help you find material fast Contains the most up-to-date information on the Windows 9 operating system Provides coverage of Windows 8.1 for those who aren't early adopters If you've just purchased your first computer or laptop need a plain-English introduction to getting started, Computers For Seniors For Dummies has you covered.



Coding For Dummies

Coding For Dummies Author Nikhil Abraham
ISBN-10 9781119296072
Release 2016-05-27
Pages 288
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Coding For Dummies, (9781119293323) was previously published as Coding For Dummies, (9781118951309). While this version features a new Dummies cover and design, the content is the same as the prior release and should not be considered a new or updated product. Hands-on exercises help you learn to code like a pro No coding experience is required for Coding For Dummies, your one-stop guide to building a foundation of knowledge in writing computer code for web, application, and software development. It doesn't matter if you've dabbled in coding or never written a line of code, this book guides you through the basics. Using foundational web development languages like HTML, CSS, and JavaScript, it explains in plain English how coding works and why it's needed. Online exercises developed by Codecademy, a leading online code training site, help hone coding skills and demonstrate results as you practice. The site provides an environment where you can try out tutorials built into the text and see the actual output from your coding. You'll also gain access to end-of-chapter challenges to apply newly acquired skills to a less-defined assignment. So what are you waiting for? The current demand for workers with coding and computer science skills far exceeds the supply Teaches the foundations of web development languages in an easy-to-understand format Offers unprecedented opportunities to practice basic coding languages Readers can access online hands-on exercises and end-of-chapter assessments that develop and test their new-found skills If you're a student looking for an introduction to the basic concepts of coding or a professional looking to add new skills, Coding For Dummies has you covered.



Introduction to the Theory of Computation

Introduction to the Theory of Computation Author Michael Sipser
ISBN-10 9781285401065
Release 2012-06-27
Pages 504
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Now you can clearly present even the most complex computational theory topics to your students with Sipser's distinct, market-leading INTRODUCTION TO THE THEORY OF COMPUTATION, 3E. The number one choice for today's computational theory course, this highly anticipated revision retains the unmatched clarity and thorough coverage that make it a leading text for upper-level undergraduate and introductory graduate students. This edition continues author Michael Sipser's well-known, approachable style with timely revisions, additional exercises, and more memorable examples in key areas. A new first-of-its-kind theoretical treatment of deterministic context-free languages is ideal for a better understanding of parsing and LR(k) grammars. This edition's refined presentation ensures a trusted accuracy and clarity that make the challenging study of computational theory accessible and intuitive to students while maintaining the subject's rigor and formalism. Readers gain a solid understanding of the fundamental mathematical properties of computer hardware, software, and applications with a blend of practical and philosophical coverage and mathematical treatments, including advanced theorems and proofs. INTRODUCTION TO THE THEORY OF COMPUTATION, 3E's comprehensive coverage makes this an ideal ongoing reference tool for those studying theoretical computing. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.