[unable to retrieve full-text content]We rank 23 open-source deep learning libraries that are useful for Data Science. The ranking is based on equally weighing its three components: Github and Stack Overflow activity, as well as Google search results.
Original Post: Ranking Popular Deep Learning Libraries for Data Science
[unable to retrieve full-text content]This article will take you through all steps required to build a simple feed-forward neural network in TensorFlow by explaining each step in details.
Original Post: TensorFlow: Building Feed-Forward Neural Networks Step-by-Step
[unable to retrieve full-text content]This post includes 5 specific video-based options for furthering your understanding of neural networks and deep learning, collectively consisting of many, many hours of insights.
Original Post: 5 Free Resources for Furthering Your Understanding of Deep Learning
[unable to retrieve full-text content]Use the code KDNUGGETS to save an additional 20% on our San Francisco events. Sign up before the end of Early Bird registration (tomorrow, October 20) and you will save on top of the RE•WORK discount!
Original Post: Learn from Tesla, Google Brain, & Facebook – KDnuggets offer
[unable to retrieve full-text content]What is an artificial neural network? How does it work? What types of artificial neural networks exist? How are different types of artificial neural networks used in natural language processing? We will discuss all these questions in the following article.
Original Post: 7 Types of Artificial Neural Networks for Natural Language Processing
[unable to retrieve full-text content]Also Collecting #DataScience Cheat Sheets; Luminoth: Open source toolkit for #ComputerVision.
Original Post: Top KDnuggets tweets, Oct 11-17: Natural Stupidity is more Dangerous than #ArtificialIntelligence; A Beginners Guide to #DeepLearning
[unable to retrieve full-text content]The most anticipated aspect of the RE•WORK Deep Learning Summit Montreal was the assembly of deep learning pioneers Yoshua Bengio, Yann LeCun, and Geoff Hinton on stage separately and together for the first time at such an event.
Original Post: Key Trends and Takeaways from RE•WORK Deep Learning Summit Montreal – Part 2: The Pioneers
[unable to retrieve full-text content]Want to Become a Data Scientist? Read This Interview First; Natural Stupidity is more Dangerous than Artificial Intelligence; Random Forests(r), Explained; Key Trends and Takeaways from RE-WORK Deep Learning Summit Montreal; An Overview of 3 Popular Courses on Deep Learning
Original Post: KDnuggets™ News 17:n40, Oct 18: Want to Become a Data Scientist? Read This!; Natural Stupidity is more Dangerous than Artificial Intelligence
[unable to retrieve full-text content]At the Deep Learning Summit in Montreal last week, we saw Yoshua Bengio, Yann LeCun and Geoffrey Hinton come together to share their most cutting edge research progressions as well as discussing the landscape of AI and the deep learning ecosystem in Canada.
Original Post: RE•WORK Deep Learning Summit Montreal Panel of Pioneers Interview: Yoshua Bengio, Yann LeCun, Geoffrey Hinton
[unable to retrieve full-text content]After completing the 3 most popular MOOCS in deep learning from Fast.ai, deeplearning.ai/Coursera (which is not completely released) and Udacity, I believe a post about what you can expect from these 3 courses will be useful for future Deep learning enthusiasts.
Original Post: An Overview of 3 Popular Courses on Deep Learning