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Published on Nov 29, 2014
Agile Machine Learning for Recommender Systems
What can data scientists and machine learning engineers learn from software developers? When it comes to process and tools, and managing complexity, the answer is: quite a bit. When we first started to deploy machine learning at if(we), it felt like we hit a speed bump in the middle of the highway. Accustomed to shipping software to millions of members multiple times a day, to constantly iterating toward better products, we were stunned at how long it took us to try new ideas using available machine learning tools. I will share what what we’ve learned from applying agile software development principles to building recommender systems, describing the tools and platforms that allow us to go from new ideas to proven product improvements in just a few days.