Issue #206

June 21, 2023

This week’s Data Science Book, "Network Science with Python", by D. Knickerbocker, is a highly recommended book for anyone interested in network analysis. It provides a comprehensive and accessible introduction to the topic. The book's linear progression and friendly tone make it highly engaging and easy to follow. The author's contagious enthusiasm and practical examples effectively communicate the power and importance of network analysis. The book covers various domains, including language and social media data mining, and explores the relationship between NLP and networks, an approach similar to our very own Graphs for Data Science substack. It emphasizes the value of actionable insights in the conversational AI domain and provides historical context and real-world use cases for NLP solutions. The book also introduces the Python packages used and dives into network science using the NetworkX library. It demonstrates how graphs can be used in machine learning and covers important concepts like betweenness centrality, page rank, and community detection with real-world applications. Overall, "Network Science with Python" is a well-written and comprehensive guide that offers practical insights and is suitable for readers of all levels.

Network Science with Python

1. Emerging Architectures for LLM Applications [a16z.com]
2. Migrating Netflix to GraphQL Safely [netflixtechblog.com]
3. Parsing more than 10TB of GitHub Logs with Trickest and Extracting Public Details of all GitHub Users & Repositories [trickest.com]
4. 8 annoying A/B testing mistakes every engineer should know [posthog.com]
5. The Secret Sauce behind 100K context window in LLMs: all tricks in one place [blog.gopenai.com]
6. Processing Medical Images At Scale On The Cloud [tweag.io]
7. Comparing Adobe Firefly, Dalle-2, OpenJourney, Stable Diffusion, and Midjourney [blog.usmanity.com]

• Predicting the antigenic evolution of SARS-COV-2 with deep learning (W. Han, N. Chen, X. Xu, A. Sahil, J. Zhou, Z. Li, H. Zhong, E. Gao, R. Zhang, Y. Wang, S. Sun, P. P.-H. Cheung, X. Gao)
• Distinguishing Simple and Complex Contagion Processes on Networks (G. Cencetti, D. A. Contreras, M. Mancastroppa, A. Barrat)
• Suboptimality in DeFi (A. Yaish, M. Dotan, K. Qin, Aviv Zohar, A. Gervais)
• The use of networks in spatial and temporal computational models for outbreak spread in epidemiology: A systematic review (L. Pujante-Otalora, B. Canovas-Segura, M. Campos, J. M. Juarez)
• Epidemic spreading in group-structured populations (S. Patwardhan, V. K. Rao, S. Fortunato, F. Radicchi)
• Identifying key players in dark web marketplaces (E. F. dos Reis, A. Teytelboym, A. ElBahraw, I. De Loizaga, A. Baronchelli)
• The temporal dynamics of group interactions in higher-order social networks (I. Iacopini, M. Karsai, A. Barrat)

Forecasting with the FB Prophet Model

June 21, 2023

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