18 Great Deep Learning Resources, most free

18 Great Deep Learning Resources, most free

Deep Learning is one of the hottest topics in data science if not all of innovative technology. Deep learning is being hyped as the solution to all types of problems, including:

1. Video Recognition - finding and/or identifying specific items in videos or images

2. Self-Driving Cars - just like it says, cars that drive without humans

3. Natural Language Processing - getting computers to understand human vocal languages

4. And others - A free book chapter on many applications of deep learning

Below are some helpful resources to get you "up-to-speed" on the world of deep learning.

Software

1. H2O - An open source platform for scalable and fast machine learning with a focus on big data and deep learning. Support for Java, Python, Scala, and R

2. Deeplearning4j - A very popular Java library for deep learning, it integrates with Hadoop and Spark.

3. Caffe - A deep learning framework built by Yangqing Jia during his graduate studies, now maintained by Berkeley. It has a focus on images and GPUs.

4. Theano - A python deep learning library.

News/Blog/Tutorials

1. Deep Learning News - Keep up with all the latest news, blogs, articles, and startups dealing with deep learning. Similar to Hacker News or Datatau, but only for deep learning material

2. Deep Learning Tutorial from Stanford - The official deep learning tutorial from the Stanford Computer Science Department's Deep Learning Group.

Journal Articles

1. The Learning Machines (Nature, Jan 2014) - Provides a very introductory view of what deep learning is and what it can do.

2. Deep Learning (Review Article in Nature, May 2015) by Yann LeCun, Yoshua Bengio, and Geoffrey Hinton

3. Growing Pains in Deep Learning (in Communications of the ACM, July 2015)

4. Deep Learning in Neural Networks (October 2014) - This technical report provides an overview of deep learning and related techniques with a special focus on developments in recent years.

Courses

1. Neural Networks for Machine Learning - Geoffrey Hinton's Coursera Class. The course ran live back in 2012, but all the videos/assignments are still available. Plus, the forums are still active, so people are still engaging in the course.

2. Oxford Deep Learning - Complete set of videos for a course taught by Nando de Freitas at Oxford in early 2015.

Books

1. Deep Learning - A textbook by Yoshua Bengio, Ian Goodfellow and Aaron Courville. A free version is available online.

2. Neural Networks and Deep Learning - A book being written by Michael Nielsen. He is releasing the book, free, one chapter at a time while he writes the book.

So, there you have it. Good luck with deep learning.

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