Daniel Géron

Machine Learning With Python Daniel Géron

Do you want to learn how machine learning and neural networks work quickly and simply? Do you want to know how to build a machine learning model, and you have no programming skills? Do you want to get started with learning data science?




This book is going to guide you to the basics and the principles behind machine learning. Machine learning is an active research domain and includes several different approaches. This book is going to help you understand the various methods of machine learning and neural networks. It will guide you through the steps you need to build a machine learning model.




Machine learning implies programming. This book will teach you Python programming. This book does not require any pre-programming skills. It will help to get you started in Python programming, as well as how to use Python libraries to analyze data and apply machine learning.




Overall, this book is a go-to guide for getting started in machine learning modeling using Python programming. Once you get through the book, you will be able to develop your machine learning models using Python.







Through this book, you will learn:

- Principles of machine learning

- Types of machine learning: supervised, unsupervised, semi-supervised, and reinforcement learning

- Advantages of each type of machine learning

- Principle and types of neural networks

- Steps to develop and fit artificial neural network model

- Getting started and installing Python

- Tools and platforms for Python programming

- How to use pandas, NumPy and matplotlib Python libraries

- How to develop a simple linear and logistic machine learning model

- How to build and train a multi-layer artificial neural network two ways: from scratch and using the Python libraries




Even if you don't have any background in machine learning and Python programming, this book will give you the tools to develop machine learning models.