Issue #41
March 8, 2020
- 1. Computational predictions of protein structures associated with COVID-19 [deepmind.com]
- 2. Technical Writing Courses [developers.google.com]
- 3. Seasonal ARIMA with Python [seanabu.com]
- 4. Dangerous Numbers? Teaching About Data and Statistics Using the Coronavirus Outbreak [nytimes.com]
- 5. Martingales and Markov Processes [medium.com/swlh]
- 6. Transformers are Graph Neural Networks [graphdeeplearning.github.io]
- 7. How Big Data Fails [onezero.medium.com]
- • Machines learn from biology (M. Buchanan)
- • Knowledge Graphs (A. Hogan, E. Blomqvist, M. Cochez, C. d'Amato, G. de Melo, C. Gutierrez, J. E. . Gayo, S. Kirrane, et al)
- • Statistical power for cluster analysis (E. S. Dalmaijer, C. L. Nord, D. E. Astle)
- • A Bayesian approach for detecting a disease that is not being modeled (J. M. Aronis, J. P. Ferraro, P. H. Gesteland, F. Tsui,Y. Ye, M. M. Wagner, G. F. Cooper)
- • Time Series Data Augmentation for Deep Learning: A Survey (Q. Wen, L. Sun, X. Song, J. Gao, X. Wang, H. Xu)
- • Dynamics of HIV Infection: an entropic-energetic view (R. E. R. González, P. H. Figueirêdo, S. Coutinho)
Kirstie Whitaker: The Turing Way: A how to guide for reproducible research | PyData London 2019
All our videos are also available in our YouTube playlist.
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