Issue #104

May 23, 2021

This weeks Data Science Book is " Machine Learning for Time Series Forecasting with Python " by Francesca Lazzeri. This book take a modern approach to introducing time series forecasting using practical intuitive explanations of the fundamental concepts together with Python code that covers data preparation, deep learning and end-to-end model deployment in the cloud in a hands on manner and without getting bogged down with too many mathematical details.

Machine Learning for Time Series Forecasting with Python

1. Flat Data [octo.github.com]
2. Graph Neural Networks [colab.research.google.com]
3. Simple Multiprocessing In Python: Comparing core vs libraries [cosmiccoding.com.au]
4. An Introduction to Knowledge Graphs [ai.stanford.edu]
5. Session-based Recommender Systems [blog.fastforwardlabs.com]
6. Observing My Cellphone Switch Towers [fabiensanglard.net]
7. Modern Javascript: Everything you missed over the last 10 years [turriate.com]

• The overfitted brain: Dreams evolved to assist generalization (E. Hoel)
• An Interpretable Graph-based Mapping of Trustworthy Machine Learning Research (N. Derzsy, S. Majumdar, R. Malik)
• Quantifying collective intelligence in human groups (C. Riedl, Y. Ji Kim, P. Gupta, T. W. Malone, A. W. Woolley)
• Urban Analytics: History, Trajectory, and Critique (G. Boeing, M. Batty, S. Jiang, L. Schweitzer)
• How COVID is changing the study of human behaviour (C. Aschwanden)
• Collectivism predicts mask use during COVID-19 (J. G. Lu, P. Jin, A. S. English)
• Representative Methodologies of Computational Socioeconomics (T. Zhou)
• The Complex Community Structure of the Bitcoin Address Correspondence Network (J. A. Fischer, A. Palechor, D. Dell'Aglio, A. Bernstein, C. J. Tessone)

Flask 2.0 is out!

May 23, 2021

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