Machine learning is a kind of artificial intelligence whereby a computer is taught to do a task using a neural network model. An artificial neural network, which mimics the organic neural networks of the brain, may learn to carry out a task by being fed examples of successful execution. A machine learning system may be thought of as a statistical modelling technique with the flexibility and subtlety of a neural network. The computing powers of artificial neural networks are unmatched by humans, despite the fact that they are not nearly as sophisticated or creative as human brains. To this day, machine learning remains one of the most exciting fields in data science. Due to the exponential growth of data, businesses need innovative means of data filtering and analysis. Despite the fact that the process is automated by machine learning methods, learning algorithms still need human input to create and implement. If you’re interested in a data science profession, specialising in machine learning is one of the best ways to make yourself stand out from the crowd. This book is very helpful for engineering students or people who want to learn the concepts of machine learning. In this book, there are a variety of topics that will increase the knowledge of the readers and through this book, the students can learn effectively and prepare for their examination with the concepts given in this book. This book is full of useful information written in a way that even the most beginner reader can understand. A better understanding of the concepts discussed in this book is achievable by reading it chapter by chapter since each one makes a significant contribution. After doing research in the relevant area, all of the chapters in this book were written, and readers may also expect to get a great deal of knowledge on a variety of other fields as a result of reading this book.