Daily Reads of September 2018

  1. Paper : An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation [Paper][doc2vec paper]. [27/09/2018]
  2. A good exploration might be to vist DeepDive datasets and application.[25/09/2018]
  3. Datasets pertaining to India is available at Machine Learning India.[25/09/2018]
  4. MIT Technology Review’s topic on Intelligent Machines post interesting articles from time to time[24/09/2018]
  5. Google’s AutoML – a new direction where 100x computational power is estimated to replace machine learning expertise. The Tree-Based Pipeline Optimization Tool (TPOT) was one of the very first AutoML methods and open-source software packages developed for the data science community [23/09/2018]
  6. “Deep Learning for Coders”, a free 7-week course provided by fast.AI. Covers topics such as Image recognition, CNN, Embeddings and RNN. [23/09/2018]
  7. Good article on Matrix decomposition, Singular Value Decomposition and Latent Semantic Indexing [23/09/2018]
  8. A good collection of Emotion and Sentiment lexicons.[11/09/2018]

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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