Issue #38
February 16, 2020
- 1. Unprecedented Facebook URLs Dataset now Available for Academic Research [socialscience.one]
- 2. Understanding Causal Inference [blog.dominodatalab.com]
- 3. Quantifying Independently Reproducible Machine Learning [thegradient.pub]
- 4. Turing-NLG: A 17-billion-parameter language model by Microsoft [microsoft.com]
- 5. Towards a general theory of "adversarial examples," the bizarre, hallucinatory motes in machine learning's all-seeing eye [boingboing.net]
- 6. Data Science, AI and Hype cycles [finextra.com]
- 7. Using Dynamic Time Warping and MLflow to Detect Sales Trends [databricks.com]
- 8. Geolocation and Geocodes in Python [medium.com/better-programming]
- • SciPy 1.0: fundamental algorithms for scientific computing in Python (P. Virtanen, R. Gommers, SciPy 1.0 Contributors)
- • Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence (S. Raschka, J. Patterson, C. Nolet)
- • fastai: A Layered API for Deep Learning (J. Howard, S. Gugger)
- • Metrics for graph comparison: A practitioner's guide (P. Wills, F. G. Meyer)
- • Ten Research Challenge Areas in Data Science (J. M. Wing)
- • Opinion: Sustainable development must account for pandemic risk (M. Di Marco, M. L. Baker, P. Daszak, P. De Barro, E. A. Eskew, C. M. Godde, T. D. Harwood, M. Herrero, A. J. Hoskins, E. Johnson, W. B. Karesh, C. Machalaba, J. N. Garcia, D. Paini, R. Pirzl, M. S. Smith, C. Zambrana-Torrelio, S. Ferrier)
- • Science through Wikipedia: A novel representation of open knowledge through co-citation networks (W. Arroyo-Machado, D. Torres-Salinas, E. Herrera-Viedma, E. Romero-Frías)
- • Predicting the Speed of Epidemics Spreading in Networks (S. Moore, T. Rogers)
- • Hypergraphs: an introduction and review (X. Ouvrard)
Implementing a SIR Disease Model in Python [1/2]
All our videos are also available in our YouTube playlist.
Enjoy the newsletter?
Forward it to a friend, or subscribe to get it straight to your inbox.
Subscribe Free