Issue #153
May 1, 2022
- 1. 5 Powerful Study Tips From Richard Feynman [piggsboson.medium.com]
- 2. Creating Confidence Intervals for Machine Learning Classifiers [sebastianraschka.com]
- 3. How I Got a Computer Science Degree in 3 Months for Less Than $5000 [miguelrochefort.com]
- 4. Against Bayesianism [josephnoelwalker.com]
- 5. It Took Me 10 Years to Understand Entropy, Here is What I Learned [cantorsparadise.com]
- 6. 3 Python Packages that will change Data Science [medium.com/trymito]
- 7. Python GroupBy Tricks [medium.com/codex]
- 8. All Roads Lead to Rome: The Machine Learning Job Market in 2022 [evjang.com]
- • Smart cities and citizen engagement: Evidence from Twitter data analysis on Italian municipalities (S. Blasia, E. Gobbo, S. R. Sedita)
- • Quantifying daily rhythms with non-negative matrix factorization applied to mobile phone data (T. Aledavood, I. Kivimäki, S. Lehmann, J. Saramäki)
- • Can brain scans reveal behaviour? Bombshell study says not yet (E. Callaway)
- • Reinforced Causal Explainer for Graph Neural Networks (X. Wang, Y. Wu, A. Zhang, F. Feng, X. He, T.-S. Chua)
- • Colossal-AI: A Unified Deep Learning System For Large-Scale Parallel Training (Z. Bian, H. Liu, B. Wang, H. Huang, Y. Li, C. Wang, F. Cui, Y. You)
- • Maximum Flow and Minimum-Cost Flow in Almost-Linear Time (L. Chen, R. Kyng, Y. P. Liu, R. Peng, M. P. Gutenberg, S. Sachdeva)
- • TeleGraph: A Benchmark Dataset for Hierarchical Link Prediction (M. Zhou, B. Li, M. Yang, L. Pan)
Intro to GraphQL for Data Scientists
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