Book Image

Machine Learning for Developers

By : Rodolfo Bonnin
Book Image

Machine Learning for Developers

By: Rodolfo Bonnin

Overview of this book

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 day-to-day application and development. You will start with the very basics of data and mathematical models in easy-to-follow 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 real-world 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.
Table of Contents (10 chapters)


GANs are a new kind of unsupervised learning model, one of the very few disrupting models of the last decade. They have two models competing with and improving each other throughout the iterations.

This architecture was originally based on supervised learning and game theory, and its main objective is to basically learn to generate realistic samples from an original dataset of elements of the same class.

It's worth noting that the amount of research on GANs is increasing at an almost exponential rate, as depicted in the following graph:

Source: The GAN Zoo (

Types of GAN applications

GANs allow new applications to produce new samples from a previous set of samples...