Depth learning portal books and resources

Depth learning portal books and resources

Bowen Address: https://blog.csdn.net/qq_31456593/article/details/90106630

Today, some machine learning and deep learning introductory books and resources for everyone. Chew bite off more than faith principle is not bad, I introduced their three machine learning and deep learning of three books (select only the best), as well as their NLP and CV classic courses.

Machine Learning:

1、Christopher Bishop教授的《Pattern Recognition and Machine Learning》

https://book.douban.com/subject/2061116/

Classic machine learning tutorials to in-depth specializes in machine learning people need to take a look.

2, Li Hang teacher "statistical learning methods."

https://book.douban.com/subject/10590856/

Machine learning entry required books, the more time the more aware of machine learning to explain refined place.

3, Zhou Zhihua teacher's "machine learning"

https://book.douban.com/subject/26708119/

Machine learning good introductory book, systematically and comprehensively

Depth study

4, Ian Goodfellow Gangster "deep learning"

https://book.douban.com/subject/26883982/

GAN author Goodfellow wrote, deep learning holy book, I read worth

5, Qiuxi Peng teacher's "neural networks and deep learning."

https://nndl.github.io/

Chiu open source books, vivid comprehensive, highly recommended

6, CHANG teacher "One day learn to deep learning."

https://www.slideshare.net/tw_dsconf/ss-62245351?qid=108adce3-2c3d-4758-a830-95d0a57e46bc&v=&b=&from_search=3

A ppt, and Li's class as straightforward entry required

Natural Language Processing Course

CS224d: Deep Learning for Natural Language Processing

http://cs224d.stanford.edu/

Depth study of various models such as Stanford University Richard Socher mainly on the field of natural language processing

Computer Vision Course

CS231n:Convolutional Neural Networks for Visual Recognition

http://cs231n.stanford.edu/

Application Stanford University Fei-Fei Li Andrej Karpathy etc. mainly on CNN, RNN in the field of image

Depth learning framework

Tensorflow

https://www.tensorflow.org

Tensorflow official website

ps: mainly tensorflow1.x previous books, and there are no books tensorflow2, if you read Chinese, you can look at my github Chinese Course:

https://github.com/czy36mengfei/tensorflow2_tutorials_chinese (cheeky self recommend)

Pytorch

https://pytorch.org/

Pytorch official website

related resources:

If you want an electronic version of books and video lessons, I am concerned about the number of public DoitNLP, reply "deep learning portal" to get