Issue #30
December 22, 2019
- 1. The Machines Are Learning, and So Are the Students [nytimes.com]
- 2. Google's AI Chief Wants to Do More With Less (Data) [wired.com]
- 3. A comprehensive guide to OCR with Tesseract, OpenCV and Python [nanonets.com]
- 4. Probability and Information Theory with Tensorflow [adhiraiyan.org]
- 5. This AI researcher is trying to ward off a reproducibility crisis [nature.com]
- • Nine quick tips for analyzing network data (V. Miele, C. Matias, S. Robin, S. Dray)
- • Fact-checking strategies to limit urban legends spreading in a segregated society (M. Tambuscio, G. Ruffo)
- • On the Bias-Variance Tradeoff: Textbooks Need an Update (B. Neal)
- • Extending Machine Language Models toward Human-Level Language Understanding (J. L. McClelland, F. Hill, M. Rudolph, J. Baldridge, H. Schütze)
- • A Bayesian Approach to Rule Mining (L. I. L. González, A. Derungs, O. Amft)
- • Ten AI Stepping Stones for Cybersecurity (R. Morla)
Jeffrey Yau: Applied Time Series Econometrics in Python and R | PyData San Francisco 2016
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