Daily Reads of September 2018

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  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]

What is your take on this topic?