Book description
Your onestop guide to becoming a Machine Learning expert.
About This Book
 Learn to develop efficient and intelligent applications by leveraging the power of Machine Learning
 A highly practical guide explaining the concepts of problem solving in the easiest possible manner
 Implement Machine Learning in the most practical way
Who This Book Is For
This book will appeal to any developer who wants to know what Machine Learning is and is keen to use Machine Learning to make their daytoday apps fast, high performing, and accurate. Any developer who wants to enter the field of Machine Learning can effectively use this book as an entry point.
What You Will Learn
 Learn the math and mechanics of Machine Learning via a developerfriendly approach
 Get to grips with widely used Machine Learning algorithms/techniques and how to use them to solve real problems
 Get a feel for advanced concepts, using popular programming frameworks.
 Prepare yourself and other developers for working in the new ubiquitous field of Machine Learning
 Get an overview of the most well known and powerful tools, to solve computing problems using Machine Learning.
 Get an intuitive and downtoearth introduction to current Machine Learning areas, and apply these concepts on interesting and cuttingedge problems.
In Detail
Most of us have heard about the term Machine Learning, but surprisingly the question frequently asked by developers across the globe is, ?How do I get started in Machine Learning??. One reason could be attributed to the vastness of the subject area because people often get overwhelmed by the abstractness of ML and terms such as regression, supervised learning, probability density function, and so on. This book is a systematic guide teaching you how to implement various Machine Learning techniques and their daytoday application and development.
You will start with the very basics of data and mathematical models in easytofollow language that you are familiar with; you will feel at home while implementing the examples. The book will introduce you to various libraries and frameworks used in the world of Machine Learning, and then, without wasting any time, you will get to the point and implement Regression, Clustering, classification, Neural networks, and more with fun examples. As you get to grips with the techniques, you'll learn to implement those concepts to solve realworld scenarios for ML applications such as image analysis, Natural Language processing, and anomaly detections of time series data.
By the end of the book, you will have learned various ML techniques to develop more efficient and intelligent applications.
Style and approach
This book gives you a glimpse of Machine Learning Models and the application of models at scale using clustering, classification, regression and reinforcement learning with fun examples. Handson examples will be presented to understand the power of problem solving with Machine Learning and Advanced architectures, software installation, and configuration.
Publisher resources
Table of contents
 Preface

Introduction  Machine Learning and Statistical Science
 Machine learning in the bigger picture
 Tools of the trade–programming language and libraries
 Basic mathematical concepts
 Summary
 The Learning Process
 Clustering

Linear and Logistic Regression
 Regression analysis
 Linear regression
 Data exploration and linear regression in practice
 Logistic regression
 Summary
 References
 Neural Networks
 Convolutional Neural Networks
 Recurrent Neural Networks
 Recent Models and Developments
 Software Installation and Configuration
Product information
 Title: Machine Learning for Developers
 Author(s):
 Release date: October 2017
 Publisher(s): Packt Publishing
 ISBN: 9781786469878
You might also like
book
40 Algorithms Every Programmer Should Know
Learn algorithms for solving classic computer science problems with this concise guide covering everything from fundamental …
book
Python Machine Learning Cookbook  Second Edition
Discover powerful ways to effectively solve realworld machine learning problems using key libraries including scikitlearn, TensorFlow, …
book
Machine Learning Algorithms  Second Edition
An easytofollow, stepbystep guide for getting to grips with the realworld application of machine learning algorithms …
book
HandsOn Machine Learning with ScikitLearn, Keras, and TensorFlow, 2nd Edition
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. …