Issue #124

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. The Math of the Amazing Sandpile [nautil.us]
2. Explaining explaining: a quick guide on explanatory writing [lucasfcosta.com]
3. How to Train Large Deep Learning Models as a Startup [assemblyai.com]
4. My Logging Best Practices [tuhrig.de]
5. Word-aligned Bloom filters [lemire.me]
6. How Much Information Can a Small Image Contain? [camerongordon.site]
7. How climate models got so accurate they earned a Nobel Prize [nationalgeographic.com]
8. Yann LeCun’s Deep Learning Course at CDS [cds.nyu.edu]
9. Faster Python with Guido van Rossum [softwareatscale.dev]
10. Introducing TensorFlow Similarity [blog.tensorflow.org]

• Switchover phenomenon induced by epidemic seeding on geometric networks (G. Ódor, D. Czifra, J. Komjáthy, L. Lovász, M. Karsai)
• Clusters of science and health related Twitter users become more isolated during the COVID-19 pandemic (F. Durazzi, M. Müller, M. Salathé, D. Remondini)
• Local time of random walks on graphs (V. Zatloukal)
• Evaluating the role of community detection in improving influence maximization heuristics (L. Hajdu, M. Krész, A. Bóta)
• The physics of higher-order interactions in complex systems (F. Battiston, E. Amico, A. Barrat, G. Bianconi, G. F. de Arruda, B. Franceschiello, I. Iacopini, S. Kéfi, V. Latora, Y. Moreno, M. M. Murray, T. P. Peixoto, F. Vaccarino, G. Petri)
• Disinformed social movements: A large-scale mapping of conspiracy narratives as online harms during the COVID-19 pandemic (P. Darius, M. Urquhart)
• On a distance-constrained graph labeling to model cooperation (J. P. Georges, K. Kuenzel, D. W. Mauro, P. S. Skardal)
• Inequality and Inequity in Network-based Ranking and Recommendation Algorithms (L. Espín-Noboa, C. Wagner, M. Strohmaier, F. Karimi)
• Sentiment and structure in word co-occurrence networks on Twitter (M. I. Fudolig, T. Alshaabi, M. V. Arnold, C. M. Danforth, P. S. Dodds)
• Social physics (M. Jusup, P. Holme, K. Kanazawa, M. Takayasu, I. Romic, Z. Wang, S. Gecek, T. Lipic, B. Podobnik, L. Wang, W. Luo, T. Klanjscek, J. Fan, S. Boccaletti, M. Perc)
• Machine-Learning media bias (S. D'Alonzo, M. Tegmark)

Docker Tutorial for Beginners

July 4, 2021

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