PythonDeepLearning

Table of Contents Python Deep Learning Credits About the Authors About the Reviewer www.PacktPub.com eBooks, discount offers, and more Why subscribe? Customer Feedback Preface What this book covers What you need for this book Who this book is for Conventions Reader feedback Customer support Downloading the example code Downloading the color images of this book Errata Piracy Questions 1. Machine Learning – An Introduction What is machine learning? Different machine learning approaches Supervised learning Unsupervised learning Reinforcement learning Steps Involved in machine learning systems Brief description of popular techniques/algorithms Linear regression Decision trees K-means Naïve Bayes What is a data product? Training Weights initialization Parallel SGD using HOGWILD! Adaptive learning Rate annealing Momentum Nesterov's acceleration Newton's method Adagrad Adadelta Distributed learning via Map/Reduce Sparkling Water Testing Model validation Labeled Data Unlabeled Data Summary of validation Hyper-parameters tuning End-to-end evaluation A/B Testing A summary of testing Deployment POJO model export Anomaly score APIs ......