Issue #107
June 13, 2021
This weeks Data Science Book is " Data Science on AWS " by Chris Fregly and Antje Barth. We've all had the experience of running out of memory or compute power while performing our data analysis or training our models. In this extremely well written book, the authors introduce us to a huge slate of AWS services that we can use to train, develop and, eventually, deploy our Machine Learning models. Overall, the book strikes the right balance between technical depth and practical breadth and will put the power of AWS at our allowing you to put your data science capabilities on par with some of the leaders of the field.
- 1. The memory models that underlie programming languages [canonical.org]
- 2. A Lifetime of Systems Thinking [thesystemsthinker.com]
- 3. Peter Norvig: Singularity is in the eye of the beholder [wandb.ai]
- 4. U.S. Launches Task Force to Study Opening Government Data for AI Research [wsj.com]
- 5. The Fermi-Pasta-Ulam-Tsingou Problem: A Foray Into The Beautifully Simple And The Simply Beautiful [3quarksdaily.com]
- 6. Git for Computer Scientists [eagain.net]
- 7. Napkin - Backend in the Browser [napkin.io]
- • A Bayesian machine scientist to aid in the solution of challenging scientific problems (R. Guimerà, I. Reichardt, A. Aguilar-Mogas, F. A. Massucci, M. Miranda, J. Pallarès, M. Sales-Pardo)
- • Temperature and population density influence SARS-CoV-2 transmission in the absence of nonpharmaceutical interventions (T. P. Smith, S. Flaxman, A. S. Gallinat, S. P. Kinosian, M. Stemkovski, H. J. T. Unwin, O. J. Watson, C. Whittaker, L. Cattarino, I. Dorigatti, M. Tristem, W. D. Pearse)
- • The physics of financial networks (M. Bardoscia, P. Barucca, S. Battiston, F. Caccioli, G. Cimini, D. Garlaschelli, F. Saracco, T. Squartini, G. Caldarelli)
- • Physics-informed machine learning (G. E. Karniadakis, I. G. Kevrekidis, L. Lu, P. Perdikaris, S. Wang, L. Yang)
- • Theoretical Modeling of Communication Dynamics (J. Berner, P. Grohs, G. Kutyniok, P. Petersen)
- • Quantifying efficient information exchange in real network flows (G. Bertagnolli, R. Gallotti, M. De Domenico)
- • Linking Twitter and survey data: asymmetry in quantity and its impact (T. A. Baghal, A. Wenz, L. Sloan, C. Jessop)
Visualization with Seaborn
All our videos are also available in our YouTube playlist.
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