【文件属性】:
文件名称:MIT.Press.Deep.Learning.2016
文件大小:77.75MB
文件格式:PDF
更新时间:2019-05-06 09:27:04
Deep Learning
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.
Table of Contents
Chapter 1 Introduction
Part I: Applied Math and Machine Learning Basics
Chapter 2 Linear Algebra
Chapter 3 Probability and Information Theory
Chapter 4 Numerical Computation
Chapter 5 Machine Learning Basics
Part II: Modern Practical Deep Networks
Chapter 6 Deep Feedforward Networks
Chapter 7 Regularization
Chapter 8 Optimization for Training Deep Models
Chapter 9 Convolutional Networks
Chapter 10 Sequence Modeling: Recurrent and Recursive Nets
Chapter 11 Practical Methodology
Chapter 12 Applications
Part III: Deep Learning Research
Chapter 13 Linear Factor Models
Chapter 14 Autoencoders
Chapter 15 Representation Learning
Chapter 16 Structured Probabilistic Models for Deep Learning
Chapter 17 Monte Carlo Methods
Chapter 18 Confronting the Partition Function
Chapter 19 Approximate Inference
Chapter 20 Deep Generative Models
网友评论
- 逻辑很清楚,循序渐进,逐步深入,是本好教材
- 这本书很全面的,是MIT的内部学习教材,全英文的