Issue #37
February 9, 2020
- 1. Layer Cake, a graphics framework for more flexible web graphics [flowingdata.com]
- 2. AI for AI: Metareasoning for modular computing systems [microsoft.com]
- 3. Ethics guidelines for trustworthy AI [ec.europa.eu]
- 4. Handling Big Datasets for Machine Learning [towardsdatascience.com]
- 5. Data Compression for Large-Scale Streaming Experimentation [netflixtechblog.com]
- 6. Time Series Cross-validation — a walk forward approach in python [medium.com/eatpredlove]
- • The role of worldviews in the governance of sustainable mobility (F. Chuang, E. Manley, A. Petersen)
- • On Geometry of Information Flow for Causal Inference (S. Surasinghe, E. M. Bollt)
- • Machine learning for asymmetric catalysis (J. Yeston)
- • A Tutorial on Learning With Bayesian Networks (D. Heckerman)
- • Solving Billion-Scale Knapsack Problems (X. Zhang, F. Qi, Z. Hua, S. Yang)
- • Radioactive data: tracing through training (A. Sablayrolles, M. Douze, C. Schmid, H. Jégou)
- • A Dataset for GitHub Repository Deduplication (D. Spinellis, Z. Kotti, A. Mockus)
MIT Introduction to Deep Learning | 6.S191
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