Issue #116

July 4, 2021

This weeks Data Science Book is the most excellent "Feynman's Lectures on Computation" by R. P. Feynman. You might be familiar with Feynman's Lectures on Physics, but his lectures on Computation (based on a class he taught and his work in 'Connection Machine') aren't any less amazing. Through this short book, Feynman guides us through the concept of computation and the van Neumann architecture in his unique style, from logic functions, to Turing machines, coding and even quantum computers. While not directly related to Data Science, it will give you a unique appreciation of the finer points in which computers are "Dumb as hell but go like mad" so that you can better squeeze every bit of performance out of your code.

Feynman's Lectures on Computation

1. Introduction to Deep Learning [sebastianraschka.com]
2. Bloom Filters - Much, much more than a space efficient hashmap! [boyter.org]
3. The Empirical and Data-Driven Revolution [thegradient.pub]
4. Geometric Deep Learning [geometricdeeplearning.com]
5. ConnectorX: The fastest library for loading your Python data frame [towardsdatascience.com]
6. Building architectures that can handle the world’s data [deepmind.com]
7. How to Detect Seasonality, Outliers, and Changepoints in Your Time Series [towardsdatascience.com]
8. The art of science [nature.com]
9. Data Monetization 101 [linkedin.com/pulse]

• Lessons from arXiv’s 30 years of information sharing (P. Ginsparg)
• Deep learning of contagion dynamics on complex networks (C. Murphy, E. Laurence, A. Allard)
• Mitigating dataset harms requires stewardship: Lessons from 1000 papers (K. Peng, A. Mathur, A. Narayanan)
• Effective epidemic containment strategy in hypergraphs (B. Jhun)
• Applications of Deep Neural Networks (J. Heaton)
• Longitudinal analysis shows durable and broad immune memory after SARS-CoV-2 infection with persisting antibody responses and memory B and T cells (K. W. Cohen, S. L. Linderman, Z. Moodie, J. Czartoski, L. Lai, et al)

Introduction to Dash Plotly

July 4, 2021

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