Issue #143

July 4, 2021

This weeks Data Science Book is "Interactive Dahsboard and Data Apps with Plotly and Dash" by E. Dabbas. In our lives as data scientists and machine learning engineers, we are often called upon to develop Dashboards and other Data Drive apps to communicate results or to monitor the performance of models deployed to production. Plotly and Dash are the current State of the Art libraries for interactive visualizations with a web frontend. This book does a remarkable job of getting you up to speed with both of these libraries taking you from basic to advanced level through practical building blocks that you can immediately customize for your own use.

Interactive Dashboard and Data Apps with Plotly and Dash

1. The House of Graphs [hog.grinvin.org]
2. A gentle introduction to automated reasoning [amazon.science]
3. Faster Python calculations with Numba [pythonspeed.com]
4. AI Overcomes Stumbling Block on Brain-Inspired Hardware [quantamagazine.org]
5. Static B-Trees [en.algorithmica.org]
6. Include diagrams in your Markdown files with Mermaid [github.blog]
7. The Unreasonableness of Math is Context Independence [bellmar.medium.com]
8. A deceptively simple plotting library for Streamlit [github.com/tvst]

• Visual object categorization in infancy (C. Spriet, E. Abassi, J.-R. Hochmann, L. Papeo)
• Quantifying NFT-driven networks in crypto art (K. Vasan, M. Janosov, A.-L. Barabási)
• Tainted ties: the structure and dynamics of corruption networks extracted from deferred prosecution agreements (T. Diviák, N. Lord)
• Outbreak Size Distribution in Stochastic Epidemic Models (J. Hindes, M. Assaf, I. B. Schwartz)
• Communicate hope to motivate the public during the COVID-19 pandemic (M. B. Petersen, L. E. Christiansen, A. Bor, M. F. Lindholt, F. Jørgensen, R. Adler-Nissen, A. Roepstorff, S. Lehmann)
• Adaptively Exploiting d-Separators with Causal Bandits (B. Bilodeau, L. Wang, D. M. Roy)
• Network Robustness Revisited (T. Gross, L. Barth)

Kubernetes: The Documentary

July 4, 2021

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