Issue #126

July 4, 2021

This weeks Data Science Book is " The Data Science Handbook " by F. Cady, data scientist at the Allen Institute for Artificial Intelligence. The proliferation of new toolkits, algorithms and approaches in Data Science make it easy to lose track of the latest developments. In this handbook, Cady presents us a comprehensive overview of the entire field. In this well written and easy to read reference the author uses practical examples and practical applications to bring the underlying theory to the real world. We feel that this book is at its most useful for when you need to quickly review a topic or to get a to the point overview of a new technique to decide whether its worth trying to apply it to your own work.

The Data Science Handbook

1. How Time Series Databases Work—and Where They Don’t [honeycomb.io]
2. A gentle introduction to the FFT [earlevel.com]
3. The Uselessness of Useful Knowledge [quantamagazine.org]
4. Bayesian histograms for rare event classification [dionhaefner.github.io]
5. Time Series Forecasting in Python [pub.towardsai.net]
6. SHAP: Explain Any Machine Learning Model in Python [towardsdatascience.com]
7. Image Encoders: BigTransfer vs CLIP [blog.alexcg.net]

• What (Exactly) is Novelty in Networks? Unpacking the Vision Advantages of Brokers, Bridges, and Weak Ties (S. Aral, P. S. Dhillon)
• From temporal network data to the dynamics of social relationships (V. Gelardi, D. Le Bail, A. Barrat, N. Claidiere)
• Mapping the NFT revolution: market trends, trade networks, and visual features (M. Nadini, L. Alessandretti, F. Di Giacinto, M. Martino, L. M. Aiello, A. Baronchelli)
• Finding disease outbreak locations from human mobility data (F. Schlosser, D. Brockmann)
• An Introduction to Probabilistic Programming (J.-W. van de Meent, B. Paige, H. Yang, F. Wood)
• Scaling of variations in traveling distances and times of taxi routes (X. Feng, H. Sun, B. Gross, J. Wu, D. Li, X. Yang, D. Zhou, Z. Gao, S. Havlin)
• Knowledge Graphs (A. Hogan, E. Blomqvist, M. Cochez, C. d'Amato, G. de Melo, C. Gutierrez, J. E. L. Gayo, S. Kirrane, S. Neumaier, A. Polleres, R. Navigli, A.-C. N. Ngomo, S. M. Rashid, A. Rula, L. Schmelzeisen, J. Sequeda, S. Staab, A. Zimmermann)

Deep Learning: A Crash Course

July 4, 2021

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