Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Repository Index
47,133 repositories indexed
1–5 of 5 · Most stars
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
Hyperparameter Experiments with TensorFlow and Keras
The world's cleanest AutoML library ✨ - Do hyperparameter tuning with the right pipeline abstractions to write clean deep learning production pipelines. Let your pipeline steps have hyperparameter spaces. Design steps in your pipeline like components. Compatible with Scikit-Learn, TensorFlow, and most other libraries, frameworks and MLOps environments.