Issue #83
December 27, 2020
- 1. How Claude Shannon Invented the Future [quantamagazine.org]
- 2. Artificial Intelligence — The Revolution Hasn’t Happened Yet [medium.com/@mijordan3]
- 3. Deep Graph Library [dgl.ai]
- 4. Probabilistic Flakiness: How do you test your tests? [engineering.fb.com]
- 5. The birth of the Web [home.cern]
- 6. Causal Models for Regression [towardsdatascience.com]
- 7. Docker for data scientists — Part 1 [towardsdatascience.com]
- • 1.2 - Simpson's Paradox
- • 1.3 - Probability Theory and Statistics
- • 1.4 - Graphs
- • 1.5 - Structural Causal Models
- • 2.2 - Chains and Forks
- • 2.3 - Colliders
- • 2.4 - d-separation
- • 2.5 - Model Testing and Causal Search
- • 3.1 - Interventions
- • 3.2 - The Adjustment Formula
- • 3.3 - Backdoor Criterion
- • 3.4 - Front-door Criterion
- • 3.5 - Conditional Interventions and Covariate-Specific Effects
- • 3.6 - Inverse Probability Weighing
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