Issue #76
November 8, 2020
- 1. A simple and interpretable performance measure for a binary classifier [memosisland.blogspot.com]
- 2. AI Expert Roadmap [i.am.ai]
- 3. Disorder Persists in Larger Graphs, New Math Proof Finds [quantamagazine.org]
- 4. Explaining Machine Learning Classifiers with LIME [towardsdatascience.com]
- 5. GroupBy in Pandas: Your Guide to Summarizing and Aggregating Data in Python [medium.com/analytics-vidhya]
- 6. AI has cracked a key mathematical puzzle for understanding our world [technologyreview.com]
- 7. Understanding Statistical Power and Significance Testing [rpsychologist.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
Enjoy the newsletter?
Forward it to a friend, or subscribe to get it straight to your inbox.
Subscribe Free