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Made-With-ML. Learn how to develop, deploy and iterate on production-grade ML applications.
49kmlops-course. Learn how to design, develop, deploy and iterate on production-grade ML applications.
3.4kfast-weights. 🏃 Implementation of Using Fast Weights to Attend to the Recent Past.
270data-engineering. Construct a modern data stack and orchestration the workflows to create high quality data for analytics and ML applications.
250monitoring-ml. Learn how to monitor ML systems to identify and mitigate sources of drift before model performance decay.
105testing-ml. Learn how to create reliable ML systems by testing code, data and models.
94the-neural-perspective. 📓 Notes from The Neural Perspective (discontinued) blog.
86casual-digressions. 💤 Old repository of notes on machine learning papers.
84attentional-interfaces. 🔍 Attentional interfaces in TensorFlow.
63feature-store. Using a feature store to connect the DataOps and MLOps workflows to enable collaborative teams to develop efficiently.
62oreilly-pytorch. 🔥 Introductory PyTorch tutorials with OReilly Media.
60GokuMohandas.
37SELU. 🤖 Implementation of Self Normalizing Networks (SNN) in PyTorch.
14follow. Jupyter Notebook
11jupyter-config. 🌍 Configuration files for Jupyter features.
11