While browsing some resources made available by the Blacksburg Data Science Meetup Group, I came across this website entitled ‘Machine Learning Mastery’. Since I have to get back to work soon, I haven’t had a chance to dive deep into its contents, but it appears to have a wealth of excellent material related to this subject. Since Deep Learning appears to be a sub-topic to Machine Learning, I’ll tag this one as Machine Learning.
Link to: Machine Learning Mastery
While researching Semantic Web topics, I have started coming across references to the field of Deep Learning. It appears to have morphed from earlier work in Neural Networks into a more evolved science. I have heard that many folks are turned off by talk of Semantic Web technology because they presume it is very related to failed work in the Neural Networks field. However, the two have different objectives, and even if they were closely related, it appears Deep Learning has taken the (presumably failed) work in Neural Nets in a new direction with productive promise. Time will tell, but it appears to be something that should be put on one’s radar screen as it involves graph analysis as does Semantic Web technology, therefore the two might be complementary technologies in future applications.
Here is a link to a free online book bearing the title of this blog post. I have yet to read its full contents, but my initial scan of its contents excited me to the point of writing this post so that I’ll have a quick reference link for my own use, and promote its availability for others on the Internet who might have a similar interest.
Neural Networks and Deep Learning, by Michael Neilsen, Dec 2014
Link to my own Deep Learning resources page