CSKrishna/Deep-Learning-NLP-Course-Work

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Created over 6 years ago
Updated over 6 years ago

CSKrishna/Deep-Learning-NLP-Course-Work

CSKrishna

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Solutions to coursework

Tree_LSTMs-for-Aspect-based-Sentiment-Analysis

Tree Structured LSTM model for sentence level aspect based sentiment analysis

Jupyter Notebook

Recommender-Systems-for-Implicit-Feedback-datasets

Matrix Factorization augmented with customer item meta data

Jupyter Notebook

Optimal-bidding-policy-using-Policy-Gradient-in-a-Multi-agent-Contextual-Bandit-setting

We use policy gradient to help agents learn optimal policies in a competitive multi-agent contextual bandit setting

Jupyter Notebook

CS294

Solutions to Deep RL assignments from CS294's Fall 2017 iteration

Jupyter Notebook

Reinforcement-Learning-Easy21

Reinforcement Learning for Easy21 (from David Silver's RL course)

Jupyter Notebook

Hierarchical-Attention-Networks

Implementation of Hierarchical Attention Network model for text classification

NER

Java code for NER based on MEMM trigram model