- NIPS 2017 Key Points & Summary Notes - Dec 18, 2017.
Third year Ph.D student David Abel, of Brown University, was in attendance at NIP 2017, and he labouriously compiled and formatted a fantastic 43-page set of notes for the rest of us. Get them here.
- 5 Free Resources for Furthering Your Understanding of Deep Learning - Oct 20, 2017.
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.
- Learning to Learn by Gradient Descent by Gradient Descent - Feb 2, 2017.
What if instead of hand designing an optimising algorithm (function) we learn it instead? That way, by training on the class of problems we’re interested in solving, we can learn an optimum optimiser for the class!
- Generative Adversarial Networks – Hot Topic in Machine Learning - Jan 3, 2017.
What is Generative Adversarial Networks (GAN) ? A very illustrative explanation of GAN is presented here with simple examples like predicting next frame in video sequence or predicting next word while typing in google search.
- Up to Speed on Deep Learning: August Update, Part 2 - Sep 23, 2016.
This is the second part of an overview of deep learning stories that made news in August. Look to see if you have missed anything.
- Embrace the Random: A Case for Randomizing Acceptance of Borderline Papers - May 16, 2016.
A case for using randomization in the selection of borderline academic papers, a particular use case which has parallels with many other possible scenarios.
- Update: Google TensorFlow Deep Learning Is Improving - Dec 17, 2015.
The recent open sourcing of Google's TensorFlow was a significant event for machine learning. While the original release was lacking in some ways, development continues and improvements are already being made.
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- Top KDnuggets tweets, Dec 17-18: Why Amazon Ratings Might Mislead You; Open Source Tools for Machine Learning - Dec 19, 2014.
Why #Amazon Ratings Might Mislead You: The Story of Herding Effects; Open Source Tools for Machine Learning; #DeepLearning Intelligence Platform - Addressing AML #Terrorism #Financing; #NIPS2014 #MachineLearning Trends: Rapid progress in #DeepLearning.