Python Deep Learning
Starting with a quick recap of important machine learning concepts, the book will delve straight into deep learning principles using Sci-kit learn. Moving ahead, you will learn to use the latest open source libraries such as Theano, Keras, Google's TensorFlow, and H20. Use this guide to uncover the difficulties of pattern recognition, scaling data with greater accuracy and discussing deep learning algorithms and techniques.
Offered by
Difficulty Level
Intermediate
Completion Time
13h32m
Language
English
About Book
Who Is This Book For?
This book is for Data Science practitioners as well as aspirants who have a basic foundational understanding of Machine Learning concepts and some programming experience with Python. A mathematical background with a conceptual understanding of calculus and statistics is also desired.
Python Deep Learning
- About Book
- Who Is This Book For?
- Book Content
Book content
chapters • 13h32m total length
Machine Learning: An Introduction
Neural Networks
Deep Learning fundamentals
Feature learning
Image recognition
Recurrent neural networks and languages models
Deep Learning for board games
Deep learning for computer Games
Anomaly detection
Building a Production-ready Intrusion Detection System
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