AI6 Cycle 2: Research-Focused Track


CS224n NLP With Deep Learning For discussions on the lecture videos and reading materials of Stanford <a href="http://web.stanford.edu/class/cs224n/">CS224n Natural Language Processing with Deep Learning</a>
Stanford CS231n CNNs for Visual Recognition For discussions on the Stanford CS231n Convolutional Neural Networks for Visual Recognition (<a href="http://cs231n.stanford.edu/">http://cs231n.stanford.edu/</a>)'s lecture videos and reading materials.
UCL Reinforcement Learning Discussions on the UCL/DeepMind course taught by David Silver on Reinforcement Learning (<a href="http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html">http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html</a>)
Deep Learning Discussions Discussions about any deep learning topic under the sun! Have an interesting idea you want to try out, a pressing question you have, or a paper you have struggled to understand for some time?

START HERE: AI6 Cycle 2: Research-Focused Track [AI6 Cycle 2: Research-Focused Track] (2)
Wiki: Lecture 2 – Word Vector Representations [CS224n NLP With Deep Learning] (1)
Wiki: Lecture 10: Neural Machine Translation and Models with Attention [CS224n NLP With Deep Learning] (1)
Wiki Lecture 3 – GloVe: Global Vectors for Word Representation [CS224n NLP With Deep Learning] (1)
Wiki: CS231n Lecture 4 – Introduction to Neural Networks [Stanford CS231n CNNs for Visual Recognition] (1)
Wiki: CS231n Lecture 3 – Loss Functions and Optimization [Stanford CS231n CNNs for Visual Recognition] (1)
Wiki: CS231n Lecture 2 – Image Classification [Stanford CS231n CNNs for Visual Recognition] (1)
Wiki: CS231n Lecture 1 - Course Introduction [Stanford CS231n CNNs for Visual Recognition] (1)
Wiki: Lecture 8: Recurrent Neural Networks and Language Models [CS224n NLP With Deep Learning] (1)
[Wiki][DISCUSS] Final Assignment Easy21 [UCL Reinforcement Learning] (1)
[Wiki] Lesson 10 Case Study: RL in Classic Games [UCL Reinforcement Learning] (1)
[Wiki] Lesson 9 Exploration and Exploitation [UCL Reinforcement Learning] (1)
[Wiki] Lesson 8 Integrating Learning and Planning [UCL Reinforcement Learning] (1)
[Wiki] Lesson 7: Policy Gradient Methods [UCL Reinforcement Learning] (1)
[Wiki] Lesson 6 Value Function Approximation [UCL Reinforcement Learning] (1)
[Wiki] Lesson 2 Markov Decision Processes [UCL Reinforcement Learning] (1)
[Wiki] Lesson 3 Dynamic Programming [UCL Reinforcement Learning] (1)
[Wiki] Lesson 4: Model-free Prediction [UCL Reinforcement Learning] (1)
[Wiki] Lesson 5 Model Free Control [UCL Reinforcement Learning] (1)
Wiki: Lecture 9: Machine Translation and Advanced Recurrent LSTMs and GRUs [CS224n NLP With Deep Learning] (1)
Wiki: Lecture 6 - Dependency Parsing [CS224n NLP With Deep Learning] (1)
Wiki: Lecture 5 - Backpropagation [CS224n NLP With Deep Learning] (1)
Wiki: Lecture 4 - Word Window Classification and Neural Networks [CS224n NLP With Deep Learning] (1)
Wiki: CS231n Lecture 7 – Training Neural Networks, part II [Stanford CS231n CNNs for Visual Recognition] (1)
Wiki: CS231n Lecture 5 – Convolutional Neural Networks [Stanford CS231n CNNs for Visual Recognition] (1)
Wiki: Lecture 16: Dynamic Neural Networks for Question Answering [CS224n NLP With Deep Learning] (1)
Wiki: Lecture 15: Coreference Resolution [CS224n NLP With Deep Learning] (1)
Wiki: Lecture 14: Tree Recursive Neural Networks and Constituency Parsing [CS224n NLP With Deep Learning] (1)
Lecture 13: Convolutional Neural Networks [CS224n NLP With Deep Learning] (1)
Wiki: Lecture 12: End-to-End Models for Speech Processing [CS224n NLP With Deep Learning] (1)