In our Delivering Your Marketplace’s Orders in Time with Machine Learning entry we talked about how important it is to track the results of Machine Learning experiments and pipelines. There are lots of parts that are constantly being tweaked and need to b... (more…)

Affirm invests in research and engineering efforts to develop ML models that are interpretable. (more…)

This talk was part of the preface event of the ECMLPKDD Teaching Machine Learning workshop. https://teaching-ml.github.io/2020/#preface-satellite-event---sep... (more…)

This post details how to harness machine learning to build a simple autoencoder with PyTorch and Filestack, using realtime user input and perceptual loss. (more…)

While debate drags on about legislation, regulations, and other measures to improve the U.S. health care system, a new wave of analytics and technology could help dramatically cut costly and unnecessary hospitalizations while improving outcomes for patien... (more…)