I wrote a whitepaper on machine learning model serving. It explains how model serving platforms can help organizations scale their machine learning capabilities efficiently. The whitepaper contains a conceptual description of what I think a model serving platform should look like. I deliberately kept out implementation details. These differ from company to company. Therefore, they are not useful to all readers. You can download the whitepaper for free from BigData Republic's website.
Netflix open sourced their internal machine learning platform Metaflow. Due to my interest in MLOps, I wanted to dive into the tool right away. Thus, I wrote a review on it. Check it out on Medium.
During my research internship, we studied the Minimum Error Correction problem. This problem has been intensively studied in the computational biology literature and is also known in the clustering literature: essentially we are required to find two cluster centres such that the sum of distances to the nearest centre, is minimized. The paper contains proofs about the computational complexity of a variant of the Minimum Error Correction problem. It was published in COCOON, the journal of computing and combinatorics.
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