Issue #9

July 28, 2019

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1. 1. Using Dynamic Time Warping and MLflow to Detect Sales Trends [databricks.com]
2. 2. Computational and Inferential Thinking [inferentialthinking.com]
3. 3. Learning web search intent representations from massive web search logs [microsoft.com]
4. 4. Text Classification: The First Step Toward NLP Mastery [medium.com]
5. 5. 5 Useful Statistics Data Scientists Need to Know [kdnuggets.com]
6. 6. A Machine Learning Guide for Average Humans [moz.com]
7. 7. Absolute Beginning into Machine Learning [hackernoon.com]
8. 8. The Human Brain Project Hasn't Lived Up to Its Promise [theatlantic.com]

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• • Quantum Computing: Lecture Notes (R. de Wolf)
• • Compositional Deep Learning (B. Gavranović)
• • Techniques for Automated Machine Learning (Y.-W. Chen, Q. Song, X. Hu)
• • Tutorial: Deriving the Standard Variational Autoencoder (VAE) Loss Function (S. Odaibo)
• • A more human approach to artificial intelligence (M. Segal)
• • Ten simple rules for writing and sharing computational analyses in Jupyter Notebooks (A. Rule, A. Birmingham, C. Zuniga, I. Altintas, S.-C. Huang, R. Knight, N. Moshiri, M. H. Nguyen, S. B. Rosenthal, F. Pérez, P. W. Rose)
• • Real-time Event Detection on Social Data Streams (M. Fedoryszak, B. Frederick, V. Rajaram, C. Zhong)
• • How to Store a Random Walk (E. Viola, O. Weinstein, H. Yu)

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