Deep Learning Series-Preface: A good tutorial for deep learning

Source: Internet
Author: User
Written before:
    busy, always in a walk stop, squeeze time, leave a chance to think.
    Intermittent, the study of deep learning also has a period of time, from the beginning of the small white to now is a primer, halfway to read a little article literature, there are many problems. The trip to Takayama has only just begun, and this series is designed to record the path and individual learning sentiment.

This article is a small note to learn some good tutorials and materials .
About Deep Learning, introductory articles and blogs are very much, writing is also very good. A summary of the blog series is the Zouxy great God article:

Deep Learning (depth learning) study notes finishing

If you are just getting into the white, it is recommended to collect this great God series of articles, this series of basic mountain covers all the basic things of deep learning, so relatively is also a comparative review of nature, a lot of details you need to have a little understanding of the ability to understand. May not understand the first time, or can only understand the very simple part, but it does not matter, it is recommended to take a look at this big review every time, each time you will have a different harvest.

If you find it hard to understand what others are writing, there are many videos on the web, such as Fudan University
Professor Wulide's

"Deep Learning course"

Very easy to understand, watching his instructional video will have a better understanding of the many underlying principles of deep learning, of course, the only problem is that the resolution of this series of videos is a bit low, it seems a little laborious, but still can learn.
About the professor's curriculum summary, there are also netizens wrote:
http://m.blog.csdn.net/blog/iichangle/44082827

Another good learning tutorial is Wunda's UFLDL tutorial, the tutorial also has a netizen translated into Chinese version, can be said to be very easy to understand, the code involved in it is also shared by netizens. About Wunda, the feeling that the study of deep learning not a few do not know, he also has a more classic machine learning tutorial, these can be described as a lower level of principles and some shallow learning algorithms, for better understanding of machine learning and even deep learning is very helpful. Deep Learning UFLDL Tutorial tutorials are as follows :

Http://ufldl.stanford.edu/wiki/index.php/UFLDL%E6%95%99%E7%A8%8B

The machine learning Tutorial URLs are as follows:

Http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=MachineLearning

The Machine learning Tutorial has an earlier version of the Stanford Classroom, where there are users to translate the Chinese subtitles, you can search for learning, very good.

There are a lot of good tutorials, of course:
Blog Park on the user summary series, when you specifically to learn a part of the time will be useful:
Http://www.cnblogs.com/tornadomeet/tag/Deep%20Learning/default.html?page=1

This netizen translates the series:
Machine learning
Its English version of the course:
Cs231n:convolutional Neural Networks for Visual recognition.

Post an ebook that is not yet published by a foreign bull:
Http://neuralnetworksanddeeplearning.com/index.html

There is also a good tutorial ( English video )
http://cl.naist.jp/~kevinduh/a/deep2014/

Then deeplearning 's official website, Inside good good things found themselves:
http://deeplearning.net/

About learning deep learning tools, there seems to be a lot of (MATLAB version, C + + version, Python version and so on Deep learning library), depending on your own familiarity. For example, a more suitable for beginners learning principle of the MATLAB version of the Toolbox:

Deeplearntoolbox
(This is followed by experiments based on the toolbox).

Toolbox under Python: Theano; deep learning Platform: Caffe and so on, these are just seen and not actually used, belong to the higher end of the deep learning application range.

The tutorial is more than a few, just to find the most important for their own, to find a good tutorial adhere to the study, will certainly have some gains.

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