Issue #144

July 4, 2021

This weeks Data Science Book is " Causality " by J. Pearl. Causal Inference is a lively and fast developing area in Data Science that we believe has the potential to be truly revolutionary in coming years (you can get a quick overview of the main ideas in our Causal Inference series over at Medium). Judea Pearl is one of the most prominent founding fathers of this field that he introduces masterfully in this textbook. While the approach Pearl chooses is mathematically rigorous, thanks to his rich use of toy examples, the key ideas and concepts are easily grasped and adapted to real world datasets. Causal Inference is a powerful arrow in any Data Scientist's quiver and this is the ideal starting point if you're interested in taking the first steps in this exciting area.

Causality

1. A Gentle Introduction to Vector Databases [frankzliu.com]
2. Machine Learning is Still Too Hard for Software Engineers [nyckel.com]
3. Time-series forecasting with MindsDB [aicoding.substack.com]
4. Explanation of Bitcoin’s Elliptic Curve Digital Signature Algorithm [suhailsaqan.medium.com]
5. These Maps Reveal the Hidden Structures of ‘Choose Your Own Adventure’ Books [atlasobscura.com]
6. Logistic Regression from Bayes' Theorem [countbayesie.com]
7. Curve fitting (non-linear least-square) to a 2D contour plot using python [nitaghosh.medium.com]
8. Just Enough Theoretical Underpinnings for NLP [opendatascience.com]

• Three Decades in Econophysics—From Microscopic Modelling to Macroscopic Complexity and Back (A. Smolyak, S. Havlin)
• Brains and algorithms partially converge in natural language processing (C. Caucheteux, J.-R. King)
• What are the Most Important Statistical Ideas of the Past 50 Years? (A. Gelman, A. Vehtari)
• Modeling Tweet Dependencies with Graph Convolutional Networks for Sentiment Analysis (A. Keramatfar, H. Amirkhani, A. J. Bidgoly)
• The metric backbone preserves community structure and is a primary transmission subgraph in contact networks (R. B. Correia, A. Barrat, L. M. Rocha)
• Graph Data Augmentation for Graph Machine Learning: A Survey (T. Zhao, G. Liu, S. Günnemann, M. Jiang)
• Three Decades of Deception Techniques in Active Cyber Defense -- Retrospect and Outlook (L. Zhang, V. L. L. Thing)

Deep Learning With PyTorch

July 4, 2021

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