Machine Learning For Dummies

Author: John Paul Mueller
Publisher: John Wiley & Sons
ISBN: 9781119245773
Size: 19.84 MB
Format: PDF, Docs
View: 11

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!

Android Apps For Absolute Beginners

Author: Wallace Jackson
Publisher: Apress
ISBN: 9781484200193
Size: 12.56 MB
Format: PDF, ePub
View: 54

Anybody can start building multimedia apps for the Android platform, and this book will show you how! Now updated to include both Android 4.4 and the new Android L, Android Apps for Absolute Beginners, Third Edition takes you through the process of getting your first Android apps up and running using 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. This book cuts through the fog of jargon and mystery that surrounds Android apps development, and gives you simple, step-by-step instructions to get you started. Teaches Android application development in language anyone can understand, giving you the best possible start in Android development Provides simple, step-by-step examples that make learning easy, allowing you to pick up the concepts without fuss Offers clear code descriptions and layout so that you can get your apps running as soon as possible This book covers both Android 4.4 (KitKat) and Android L, but is also backwards compatible to cover the previous Android releases since Android 1.5.

Android Apps For Absolute Beginners

Author: Wallace Jackson
Publisher: Apress
ISBN: 9781484222683
Size: 15.14 MB
Format: PDF, Docs
View: 18

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.

Introduction To Machine Learning With Python

Author: Andreas C. Müller
Publisher: "O'Reilly Media, Inc."
ISBN: 9781449369897
Size: 15.73 MB
Format: PDF, Docs
View: 26

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. With all the data available today, machine learning applications are limited only by your imagination. You’ll learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. Authors Andreas Müller and Sarah Guido focus on the practical aspects of using machine learning algorithms, rather than the math behind them. Familiarity with the NumPy and matplotlib libraries will help you get even more from this book. With this book, you’ll learn: Fundamental concepts and applications of machine learning Advantages and shortcomings of widely used machine learning algorithms How to represent data processed by machine learning, including which data aspects to focus on Advanced methods for model evaluation and parameter tuning The concept of pipelines for chaining models and encapsulating your workflow Methods for working with text data, including text-specific processing techniques Suggestions for improving your machine learning and data science skills

Machine Learning

Author: Ethem Alpaydin
Publisher: MIT Press
ISBN: 9780262529518
Size: 18.32 MB
Format: PDF, Docs
View: 94

A concise overview of machine learning -- computer programs that learn from data -- which underlies applications that include recommendation systems, face recognition, and driverless cars.

Make Your Own Neural Network

Author: Tariq Rashid
Publisher: Createspace Independent Publishing Platform
ISBN: 1530826608
Size: 16.73 MB
Format: PDF, Kindle
View: 20

A step-by-step gentle journey through the mathematics of neural networks, and making your own using the Python computer language. Neural networks are a key element of deep learning and artificial intelligence, which today is capable of some truly impressive feats. Yet too few really understand how neural networks actually work. This guide will take you on a fun and unhurried journey, starting from very simple ideas, and gradually building up an understanding of how neural networks work. You won't need any mathematics beyond secondary school, and an accessible introduction to calculus is also included. The ambition of this guide is to make neural networks as accessible as possible to as many readers as possible - there are enough texts for advanced readers already! You'll learn to code in Python and make your own neural network, teaching it to recognise human handwritten numbers, and performing as well as professionally developed networks. Part 1 is about ideas. We introduce the mathematical ideas underlying the neural networks, gently with lots of illustrations and examples. Part 2 is practical. We introduce the popular and easy to learn Python programming language, and gradually builds up a neural network which can learn to recognise human handwritten numbers, easily getting it to perform as well as networks made by professionals. Part 3 extends these ideas further. We push the performance of our neural network to an industry leading 98% using only simple ideas and code, test the network on your own handwriting, take a privileged peek inside the mysterious mind of a neural network, and even get it all working on a Raspberry Pi. All the code in this has been tested to work on a Raspberry Pi Zero.

An Introduction To Statistical Learning

Author: Gareth James
Publisher: Springer Science & Business Media
ISBN: 9781461471387
Size: 11.85 MB
Format: PDF, ePub, Docs
View: 64

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.