Machine Learning Guide for Beginners with Real Examples - Learn & Master ML

What is machine learning? How machine learning works? Should I use a machine learning model or another approach to solve my problem? How do I implement machine learning to my problem? What are the machine learning methods I can use for my problem? How do I know my machine learning model is efficient? Are you wondering all these questions and hesitate on how to start with machine learning? The object of this book is to answer all of these questions. This book will give an initiation to machine learning methods. In fact, this book will give the very fundamental concepts of machine learning methods with no pre-requisite skills. Machine learning include is a large domain of research and have different branches.This book will teach the concepts of machine learning in general and also how to use artificial neural networks. By acquiring the skills presented in this book, we will be able to decide if machine learning is suited to solve your problem. You will also be able to make a judgement on the best way to implement a machine learning model to solve the problem you have in hand.By reading this book you will learn:- The general concept of machine learning- When to use and when to avoid machine learning- The 4 main types of machine learning- When to use each type of machine learning- The general concept of artificial neural networks- Activation function in artificial neural network and to choose an activation function within an artificial neural network- The 5 main types of artificial neural network- The best function to be used to train artificial neural networks.- the 2 main concepts to know in the training process of the artificial neural network- the main variants and algorithms for the formation of an artificial neural network and a machine learning model in general.Even you don't have any mathematical background or a statistical skill, this book will help you develop a sound understanding of machine learning methods and artificial neural networks.