A chat with <strong>John D. Cook</strong>, a fellow ML/statistics consultant for companies like Amazon, Google, Microsoft or Amgen,  about his background, consulting for pharma and legal, project pricing, the best tool for the job vs. the cost of moving across tools, the Python language and its community, and more.

RRP #2: John D. Cook on math consulting, Python and going solo

Andreas Müller talks about how he fell in love with scikit-learn, the Python library for Machine Learning, and his continuous work there as the package maintainer. We also cover his work at Amazon and why he left to work on open source; his recent book on machine learning in Python; sustainability and future of sklearn in the "deep learning world", and his impressions of New York as a German citizen.

RRP #3: Andy Müller on scikit-learn and open source software

Leo Boytsov, a PhD researcher from the Language Technologies Institute of Carnegie Mellon University, talks about fast approximate search in modern information retrieval. We discuss the curse of dimensionality, hard-to-beat baselines and NMSLIB, Leo's super fast library for nearest-neighbour search. How does NMSLIB compare to Facebook's FAISS and Spotify's Annoy? Warning: very technical.

RRP #4: Leo Boytsov on Approximate Search and Information Retrieval

Every beginning carries within it the seed of its own destruction.

Radim

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