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WebRTC produces mountains of data that can be used to optimize streams and debug problems—if you know where to look. Chad discusses how callstats.io uses unsupervised learning to discover non-obvious issues inside the vast amount of call quality data the company collects. ML methods reviewed include feature reduction with Principal Component Analysis (PCA), Clustering with Gaussian Mixture Model (GMM), and optimizing cluster sizes with Bayesian Inference Criterion (BIC).
Presented at AllThingsRTC 2019. See the video here: https://www.youtube.com/watch?v=WCC0Vy9aRNE