Vincent Warmerdam is a data scientist and Python educator known for exploring practical data tools, developer workflows, and thoughtful software design. He regularly writes about Python, machine learning, tooling experiments, and lessons learned from real-world data work.
Shreya Shankar is a PhD researcher sharing insights on AI, machine learning, HCI, and data science. Her work explores LLM applications, AI evaluation, and practical ML engineering challenges, reaching a wide audience across blogs and social media.
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.
Kevin Markham is a data scientist, educator, and writer focused on practical machine learning, Python, and AI literacy. He’s best known for clear explanations of scikit-learn, pandas, and modern AI trends, helping practitioners stay effective without hype or overengineering.
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.
Igor Susmelj is co-founder of Lightly, an ETH Zurich spin-off focused on simplifying large-scale datasets for deep learning. He writes about data pipelines, data annotation, and efficient ML workflows.
Philipp Schmid is a Staff Engineer at Google DeepMind, building AI Developer Experience and DevRel initiatives. He specializes in LLMs, RLHF, and making advanced AI accessible to developers worldwide.
Yoel Zeldes is an algorithm engineer at AI21 Labs with a background in computer science from Hebrew University. He specializes in machine learning, NLP, computer vision, and distributed computing, focusing on data-driven solutions and clean, elegant code.
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.
Simon Willison — Independent developer and writer documenting practical experiments, tools, and deep analysis around large language models, generative AI, web development, security, and emerging programming workflows through detailed posts and daily TILs.
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.
SimonWillison.net is the long-running blog of Simon Willison, a software engineer, open-source creator, and co-author of the original Django framework. He writes about Python, Django, Datasette, AI tooling, prompt engineering, search, databases, APIs, data journalism, and practical software architecture. The blog includes detailed notes from experiments, conference talks, and real projects. Readers will find clear explanations of topics such as LLM workflows, SQL patterns, data publishing, scraping, deployment, caching, and modern developer tooling. Simon also publishes frequent micro-posts and TIL entries that document small discoveries and tricks from day-to-day engineering work. The tone is practical and research oriented, making the site a valuable resource for anyone interested in serious engineering and open data.
Piotr Migdał – Blog of a Data Explorer and Visual Storyteller This is the personal blog of Dr. Piotr Migdał, a technologist and visual storyteller with a strong background in quantum physics, deep learning, and data visualization. He is a founding engineer at Quesma, where he uses AI to turn complex datasets into clear visual insights through ggplot2 charts and Grafana dashboards. His posts combine technology, creativity, and personal reflection. You will find articles about machine learning, interactive data visualization, and projects that bridge science and art. Beyond his technical work, Piotr writes about dance, mindfulness, and the human side of creativity. This blog is a great read for developers, data scientists, and anyone interested in how technology and art can come together to explain the world in a meaningful way.
