Issue #23
November 3, 2019
- 1. Gamma Distribution — Intuition, Derivation, and Examples [medium.com/@aerinykim]
- 2. The Most Undervalued Standard Python Library [towardsdatascience.com]
- 3. Machine Learning Model for Stochastic Processes [medium.com/towards-artificial-intelligence/]
- 4. AI Principles: Recommendations on the Ethical Use of AI by the DoD [govexec.com]
- 5. Improve ml predictions using graph algorithms [slideshare.net]
- 6. Diagram of distribution relationships [johndcook.com]
- 7. Introduction to Matplotlib — Data Visualization in Python [heartbeat.fritz.ai]
- 8. Color: From Hexcodes to Eyeballs [jamie-wong.com]
- • Definitions, methods, and applications in interpretable machine learning (W. J. Murdoch, C. Singh, K. Kumbier, R. Abbasi-Asl, B. Yu)
- • Analysis of group evolution prediction in complex networks (S. Saganowski ,P. Bródka, M. Koziarski, P. Kazienko)
- • Learning by Unsupervised Nonlinear Diffusion (M. Maggioni, J. M. Murphy)
- • Detecting Fake News with Weak Social Supervision (K. Shu, A. H. Awadallah, S. Dumais, H. Liu)
- • Driving Datasets Literature Review (C.-É. N. Laflamme, F. Pomerleau, P. Giguère)
- • Toward epidemic thresholds on temporal networks: a review and open questions (J. Leitch, K. A. Alexander, S. Sengupta)
- • Bayesian Modeling of Random Walker for Community Detection in Networks (T. J. Suzuki)
- • Fundamentals of Statistical Causality (A. P. Dawid)
Why storytelling matters | Garr Reynolds | TEDxKyoto
All our videos are also available in our YouTube playlist.
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