Issue #149
July 4, 2021
This weeks Data Science Book is " Causality " by J. Pearl. Causal Inference is a lively and fast developing area in Data Science that we believe has the potential to be truly revolutionary in coming years (you can get a quick overview of the main ideas in our Causal Inference series over at Medium). Judea Pearl is one of the most prominent founding fathers of this field that he introduces masterfully in this textbook. While the approach Pearl chooses is mathematically rigorous, thanks to his rich use of toy examples, the key ideas and concepts are easily grasped and adapted to real world datasets. Causal Inference is a powerful arrow in any Data Scientist's quiver and this is the ideal starting point if you're interested in taking the first steps in this exciting area.
- 1. How I Rewired My Brain to Become Fluent in Math [nautil.us]
- 2. NVIDIA to Build Earth-2 Supercomputer to See Our Future [blogs.nvidia.com]
- 3. 5 Reasons You Should Never Use PCA For Feature Selection [blog.kxy.ai]
- 4. 7 tools for visualizing a codebase [lmy.medium.com]
- 5. Life’s Preference for Symmetry Is Like ‘A New Law of Nature’ [nytimes.com]
- 6. An Intuitive Guide to Linear Algebra [betterexplained.com]
- 7. Markov Chains for programmers [czekster.github.io]
- 8. Will Omicron finally overpower China’s COVID defences? [nature.com]
- • Agent-based modelling of reactive vaccination of workplaces and schools against COVID-19 (B. Faucher, R. Assab, J. Roux, D. Levy-Bruhl, C. T. Kiem, S. Cauchemez, L. Zanetti, V. Colizza, P.-Y. Boëlle, C. Poletto)
- • Social nucleation: Group formation as a phase transition (F. Schweitzer, G. Andres)
- • Pooled testing of traced contacts under superspreading dynamics (S. Tsirtsis, A. De, L. Lorch, M. Gomez-Rodriguez)
- • Manipulating Twitter Through Deletions (C. Torres-Lugo, M. Pote, A. Nwala, F. Menczer)
- • Turnover in close friendships: age and gender differences (C. Roy, K. Bhattacharya, R. I. M. Dunbar, K. Kaski)
- • "Born in Rome" or "Sleeping Beauty": Emergence of hashtag popularity on a microblogging site (H. Cui, J. Kertész)
- • Scaling of spatio-temporal variations of taxi travel routes (X. Feng, H. Sun, B. Gross, J. Wu, D. Li, X. Yang, Y. Lv, D. Zhou, Z. Gao, S. Havlin)
This is why Python data classes are awesome
All our videos are also available in our YouTube playlist.
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