Most of my discussions lately with CTOs and Product Managers have ended with me emailing some links and info about Deep Learning. I’m a relative newbie to the space myself so hopefully this is a good primer.
For Product Managers and CTOs, having an understanding of what’s possible with Deep Learning and how the technology could impact your features and stack is quickly becoming very important.
A great summary of Deep Learning from Lee Gomes taken from this article:
The current excitement about AI stems, in great part, from groundbreaking advances involving what are known as “convolutional neural networks.” This machine learning technique promises dramatic improvements in things like computer vision, speech recognition, and natural language processing. You probably have heard of it by its more layperson-friendly name: “Deep Learning.”
Here are few more article I like:
Albert Wenger from USV talks about Machine Intelligence
Shivon Zilis from Bloomberg Beta created a Machine Intelligence Landscape
And, here’s a list of terms to explore:
Word Embeddings
Nodes and edges
Precision and recall
Deterministic
Frame semantics
Knowledge graph
Hypernym and Hyponym
Word sense disambiguation
Hearst Patterns
GPU computing
Dropout
Stochastic Pooling
Cognitive Computing
And, some good people to follow in the Deep Learning space:
Yann LeCun – Facebook’s Director of AI Research
Geoffrey Hinton – Distinguished Researcher at Google and Distinguished Professor at University of Toronto
Yoshua Bengio – Full Professor Department of Computer Science and Operations Research
and Canada Research Chair in Statistical Learning Algorithms
Elliot Turner – Founder AlchemyAPI
Derrick Harris – Senior Writer at GigaOm
Seth Grimes – Industry Analyst
And, some websites to explore:
Google Deep Learning Community
http://www.deeplearning.net
http://www.kdnuggets.com
http://www.r-bloggers.com
http://fivethirtyeight.com
http://www.datasciencecentral.com/profiles/blogs/50-blogs-worth-reading
http://www.semanticweb.com
And finally, some awesome AI videos:
