What this book covers
Chapter 1, Unsupervised Machine Learning, shows you how to apply unsupervised learning techniques to identify patterns and structure within datasets.
Chapter 2, Deep Belief Networks, explains how the RBM and DBN algorithms work; you'll know how to use them and will feel confident in your ability to improve the quality of the results that you get out of them.
Chapter 3, Stacked Denoising Autoencoders, continues to build our skill with deep architectures by applying stacked denoising autoencoders to learn feature representations for high-dimensional input data.
Chapter 4, Convolutional Neural Networks, shows you how to apply the convolutional neural network (or Convnet).
Chapter 5, Semi-Supervised Learning, explains how to ...
Get Advanced Machine Learning with Python now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
