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Machine Learning Posts - Digest 02

This week’s articles:

  1. A 60-Minutes Course on Fairness in Machine Learning

Summary: The course focuses on the bias in machine learning because of humans! I think this is an important area of work.

  1. Model-Based Machine Learning Book

Summary: This is actually not an article but an entire book. I have read a few pages of the book but I am not at a point where I can summarize anything!

  1. Forecasting at Uber: An Introduction

Summary: Anyone with an interest in time-series analysis will find this post interesting. From the article: “we discuss the critical components of forecasting we use, popular methodologies, backtesting, and prediction intervals.”

  1. Meet Michelangelo: Uber’s Machine Learning Platform

Summary: Michelangelo is Uber’s in-house machine learning as a service platform (MLaaS). From the article, “It is designed to cover the end-to-end ML workflow: manage data, train, evaluate, and deploy models, make predictions, and monitor predictions.” Check out the use cases for Michelangelo. I found that part interesting.

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