Jake VanderPlas is an astronomer and open-source leader, serving as Director of Open Software at the University of Washington’s eScience Institute. He writes and builds widely used Python tools for data science, machine learning, and scientific computing.
Julien Jerphanion writes in-depth articles on machine learning performance, numerical computing, and software craftsmanship. His work focuses on scikit-learn internals, efficient algorithms, and building a strong theoretical understanding of ML systems.
Jay Mody is a software engineer and writer sharing clear, concise explanations of machine learning concepts and numerical computing. His blog focuses on intuition-driven deep dives into topics like GPT, attention, and efficient NumPy implementations.
Stern Semasuka is a data scientist at WestJet who writes beginner-friendly guides on machine learning, data analysis, and programming. His blog simplifies complex ML concepts using practical projects and the Feynman Technique.
Eugene Yan is a Principal Applied Scientist at Amazon, building AI-powered recommendation systems and experiences. He shares insights on RecSys, LLMs, and applied machine learning, while mentoring and investing in ML startups.
Sebastian Raschka, PhD, is an LLM Research Engineer and AI expert bridging academia and industry, specializing in large language models, high-performance AI systems, and practical, code-driven machine learning.
John D. Cook provides expert consulting in applied mathematics and data privacy, helping clients from tech, biotech, and legal industries—including Amazon, Google, Microsoft, and Amgen—solve complex problems efficiently.
SebastianRaschka.com is the personal blog of Sebastian Raschka, PhD, an LLM research engineer whose work bridges academia and industry in AI and machine learning. On his blog and notes section he publishes deep, well-documented articles on topics such as LLMs (large language models), reasoning models, machine learning in Python, neural networks, data science workflows, and deep learning architecture. Recent posts explore advanced themes like “reasoning LLMs”, comparisons of modern open-weight transformer architectures, and guides for building, training, or analyzing neural networks and model internals.
PythonSpeed.com is a blog created by Itamar Turner Trauring, a software engineer known for his work on Python performance, memory optimization, and practical tooling for data science and scientific computing. The site focuses on real production challenges: reducing memory usage, making Python code faster, profiling scientific workloads, improving Docker packaging, and understanding how to ship efficient applications. The writing is clear, measurable, and based on hands-on experience rather than theory. Itamar is the creator of Sciagraph, a performance and memory profiler for Python data science, and the author of open source tools such as Fil and Eliot, both designed to help developers understand how their code behaves. His broader mission is to support useful software development, cut CO2 emissions through faster computing, and encourage engineering that matters. Beyond technical work he is active in local bicycle safety advocacy in Cambridge, MA, helping cities adopt sustainable transportation policies. Thanks to this mix of engineering depth and real-world impact, PythonSpeed.com is one of the most practical and thoughtful resources for developers who want to make Python software faster and more efficient.
Yasoob Khalid is a developer and writer best known for the free, open-source book Intermediate Python and his project-driven follow-up, Practical Python Projects. His articles and books have reached 5+ million readers across 189+ countries, and his blog remains a go-to place for clear, practical Python insights. By day, Yasoob works on Azure Cloud Networking at Microsoft, and by night he continues to publish tutorials, notes, and experiments that demystify real-world Python for learners at every level. He’s also the author behind the long-running Python Tips site and newsletter, where he focuses on approachable explanations and hands-on examples.
