Daily Reads of November 2018

  1. A Medium article that covers the topic of visualizing high-dimensional data using PCA and t-SNE in Python [26/11/2018]
  2. Google AI open-sources BERT- A Pretraining model for NLP tasks. This mainly addresses domains that have small amount of labeled data like sentiment analysis and Question-answering. BERT is trained to produce generalized language model representation which we then train on our own tasks, now requiring much less amount of labeled data.  [article][code][02/11/2018]
  3. OpenAI develops Random Network Distillation for Reinforcement Learning, which now uses curiosity to train, instead of a future reward function or without any given objective function. [article][code] [02/11/2018]

roysoumya

Hello everyone. I am Soumyadeep. I have been working on Machine learning projects for the last 4 years. I am now pursuing Ph.D. in Computer Science Department at IIT Kharagpur. I recently completed M.S (Research) from the same department in November, 2019. My research interests involve applying Machine Learning, NLP and Deep Learning to solve Online Reputation Monitoring and Consumer Health Search problems.

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