Sitemap - 2020 - Machine Learning Ops Roundup

Issue #8: Toronto ML Summit. GPT-2. ML Feedback Loops. Explainability Struggles. Judgy AI.

Issue #7: Trustworthy AI in the Govt, re:Invent, Underspecification, Tools for Software 2.0

Issue #6: MLOps Resources. Feature Stores. Interpretability. Predictive Uncertainty.

Issue #5: Cloud ML Platforms. Disappearing Data. Data Poisoning. "Building Cars v/s Factories" for ML models

Issue #4: Data Landscape. ML Stack. Imbalanced Datasets. Search@Airbnb. Ball vs Bald?

Issue #3: State of AI. Behavioral testing ML models. Dynamic benchmarks. Data versioning. MadeWithML.

Issue #2: Nuts and Bolts of ML. Unfriendly Comments. Great Expectations. Common ML Misconceptions.

Issue #1: Why is Machine Learning so hard?

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