a mashup of Python machine learning
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How to design and train deep neural networks in Python. How to implement deep neural networks using Keras TensorFlow
Chapter 1: Machine Learning Fundamentals Chapter 2: Deep Learning Essentials ... Chapter 3: Understanding Deep Learning. Architectures ...
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AI Crash Course: A fun and hands-on introduction to machine learning reinforcement learning
Packt Publishing has endeavored to provide trademark information about all of the Module 1 Python Machine Learning
Chapter 1: Getting Started with Python Machine Learning 1 Machine learning and Python – a dream team 2 What the book will teach you (and what it will not) 3 What to do when you are stuck 4 Getting started 5 Introduction to NumPy SciPy and matplotlib 6 Installing Python 6 Chewing data efficiently with NumPy and intelligently with SciPy 6
A roadmap for building machine learning systems 11 Preprocessing – getting data into shape 12 Training and selecting a predictive model 12 Evaluating models and predicting unseen data instances 13 Using Python for machine learning 13 Installing Python and packages from the Python Package Index 14
A roadmap for building machine learning systems 10 Preprocessing – getting data into shape 11 Training and selecting a predictive model 12 Evaluating models and predicting unseen data instances 13 Using Python for machine learning 13 Installing Python packages 13 Summary 15 Chapter 2: Training Machine Learning Algorithms for Classification 17
Python Machine Learning Projects 1 Foreword 2 Setting Up a Python Programming Environment 3 An Introduction to Machine Learning 4 How To Build a Machine Learning Classi?er in Python with Scikit-learn 5 How To Build a Neural Network to Recognize Handwritten Digits with TensorFlow 6 Bias-Variance for Deep Reinforcement Learning: How To
Chapter 1: Getting Started with Python and Machine Learning 6 What is machine learning and why do we need it? 7 A very high level overview of machine learning 9 A brief history of the development of machine learning algorithms 11 Generalizing with data 13 Overfitting underfitting and the bias-variance tradeoff 14 Avoid overfitting
Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals However Packt Publishing cannot guarantee the accuracy of this information First published: August 2017 Production reference: 1210817 Published by Packt Publishing Ltd Livery Place