Issue #121

July 4, 2021

This weeks Data Science Book is " Fundamentals of Data visualization " by C. O. Wilke. Here at D4Sci we're firm believers that an image is worth 1000 words (check out V4Sci if you haven't already) and this book will quickly and easily super charge your visualization skills. Wilke brings to bear the perspective of a Data Scientist to a field often dominated by Designers. Throughout this book, Wilke teaches you how to craft powerful visualizations with your tool or programming language of choice by introducing only as much visualization theory and concepts as necessary and without getting lost in abstract ideas or concepts. The authors experience as a Data Science makes this one of the best applied books on Visualization, despite the fact that the book is entirely language agnostic.

Fundamentals of Data visualization

1. Understanding Convolutions on Graphs [distill.pub]
2. A Gentle Introduction to Graph Neural Networks [distill.pub]
3. Anomaly Detection: Why Your Data Team Is Just Not That Into It [montecarlodata.com]
4. How big science failed to unlock the mysteries of the human brain [technologyreview.com]
5. Simulating Traffic Flow in Python [towardsdatascience.com]
6. Machine Learning With Graphs: Going Beyond Tabular Data [odsc.com]
7. Machine Learning to Predict Earnings for Stocks: Support-vector Machines [medium.com/analytics-vidhya]

• Cognitive maps of social features enable flexible inference in social networks (J.-Y. Son, A. Bhandari, O. F. Hall)
• Persistence of information flow: A multiscale characterization of human brain (B. Benigni, A. Ghavasieh, A. Corso, V. d’Andrea, M. De Domenico)
• The global effectiveness of fact-checking: Evidence from simultaneous experiments in Argentina, Nigeria, South Africa, and the United Kingdom (E. Porter, T. J. Wood)
• Learning Mathematical Properties of Integers (M. Ryskina, K. Knight)
• The mathematics of adversarial attacks in AI -- Why deep learning is unstable despite the existence of stable neural networks (A. Bastounis, A. C. Hansen, V. Vlačić)
• LM-Critic: Language Models for Unsupervised Grammatical Error Correction (M. Yasunaga, J. Leskovec, P. Liang)

An Absolute Beginner's Guide to Python GeoPandas

July 4, 2021

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