Machine Learning With Python: The Ultimate Guide for Absolute Beginners with Steps to Implement Artificial Neural Networks with Real Examples (Useful Python Tools eg. Anaconda, Jupiter Notebook)

Géron, Daniel

ISBN 10: 1914306619 / ISBN 13: 9781914306617

Published by Tiger Gain LTD, 2021

About this Item

172 pages. 9.29x6.14x0.63 inches. In Stock.

Seller Inventory # zk1914306619

Bibliographic Details

• Title: Machine Learning With Python: The Ultimate Guide for Absolute Beginners with Steps to Implement Artificial Neural Networks with Real Examples (Useful Python Tools eg. Anaconda, Jupiter Notebook)
• Publisher: Tiger Gain LTD
• Publication Date: 2021
• Language: English
• ISBN 10: 1914306619
• ISBN 13: 9781914306617
• Binding: Hardcover
• Condition: Brand New
• Weight: 0.35 kilograms

About this title

Synopsis

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.