Publisher's Synopsis
Are you a novice programmer who wants to learn Python Machine Learning? Are you worried about how to translate what you already know into Python?
This book will help you overcome those problems!
As machines get ever more complex and perform more and more tasks to free up our time, so it is that new ideas are developed to help us continually improve their speed and abilities.
One of these is Python and in Python Machine Learning: 3 books in 1 - The Ultimate Beginner's Guide to Learn Python Machine Learning Step by Step using Scikit-Learn and Tensorflow, you will discover information and advice on:
Book 1
- What machine learning is
- The history of machine learning
- Approaches to machine learning
- Support vector machines
- Machine learning and neural networks
- The Internet of Things (IoT)
- The future of machine learning
- And more...
Book 2
- The principles surrounding Python
- Different types of networks so you can choose what works best for you
- Features of the system
- Real world feature engineering
- Understanding the techniques of semi-supervised learning
- And more...
Book 3
- How advanced tensorflow can be used
- Neural network models and how to get the most from them
- Machine learning with Generative Adversarial Networks
- Translating images with cross domain GANs
- TF clusters and how to use them
- How to debug TF models
- And more...
This book has been written specifically for beginners and the simple, step by step instructions and plain language make it an ideal place to start for anyone who has a passing interest in this fascinating subject. Python really is an amazing system and can provide you with endless possibilities when you start learning about it.
Get a copy of Python Machine Learning today and see where the future lies.
