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ML Experimentation Platform
Unsorted Playground for Machine Learning, Reinforcement Learning and other AI Experiments
Contains code and slides for our talk at Cloud Next 2022: Better Hardware Provisioning for ML Experiments on GCP.
A reusable codebase for fast data science and machine learning experimentation, integrating various open-source tools to support automatic EDA, ML models experimentation and tracking, model inference, model explainability, bias, and data drift analysis.
An application of the WhizML codebase for an analysis of cardiovascular disease risk.
An application of the WhizML codebase for an analysis of Walmart weekly sales.