Episode Summary: A few years ago I promised you a blog series on how to start your own consulting business in machine learning: getting set up, figuring out legal & intellectual property rights, finding consistent work, scoping in the face of research uncertainty, the project life cycle, mistakes to avoid... I gave a few talks on this topic but never ... Read More


Episode Summary: A few years ago I promised you a blog series on how to start your own consulting business in machine learning: getting set up, figuring out legal & intellectual property rights, finding consistent work, scoping in the face of research uncertainty, the project life cycle, mistakes to avoid...


I gave a few talks on this topic but never got around to writing that blog series. Today I sat down with John D. Cook, a fellow top ML/stats consultant for companies like Amazon, Google, Microsoft or Amgen, and we finally got to discuss (some of) that: John's background, his 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.


Of interest to people with a vicious streak of independence.


Links & resources:


John's consulting business: johndcook.com aka Singular Value Consulting.


John's instantly relatable, quirky and fun writings on his personal blog. RECOMMENDED!

To get a taste, check out Don't invert that matrix, R language for programmers, Statistical distributions chart / cheat-sheet, Bayesian consulting...


Twitter: John's personal @johndcook + his 18 (!!) other thematic twitter accounts.


So you want to be a data science consultant (or hire one)? (my presentation from Berlin Buzzwords 2015) and From Research to Industry, in Ten Not-So-Easy
Steps
(similar presentation from the Industry panel at SIGIR 2016).


The podcast lives on SoundCloud, plus this time I submitted it to iTunes, Stitcher and YouTube as well. I hope you like it!


Poll: In our chat, we barely scratched the surface. Which side of consulting is the most interesting to you? Let me know in the poll below and I'll cover it more. Thanks!

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What would you like to hear more about?




Administrative: international taxes, incorporation, legal, IPR, hiring & managing data science teams...





Business: ML application in various industries, project scoping, pricing research, R&D project life cycle...





Technical: ML theory and algorithms, programming, frameworks and tools, optimizing accuracy and scale...





Other: world travel, life in Asia, languages and history, time management, health... or comments below :)














Yes, that's what I want!

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