yuvalatzmon / SACRED_HyperOpt_v2
A collection of classes, methods and examples, to integrate SACRED experiment framework with hyperopt distributed training.
☆18Updated 6 years ago
Alternatives and similar repositories for SACRED_HyperOpt_v2:
Users that are interested in SACRED_HyperOpt_v2 are comparing it to the libraries listed below
- Streamlined machine learning experiment management.☆107Updated 4 years ago
- Experiment orchestration☆103Updated 4 years ago
- ☆45Updated 5 years ago
- TF 2.x and PyTorch Lightning Callbacks for GPU monitoring☆92Updated 4 years ago
- Python implementation of GLN in different frameworks☆98Updated 4 years ago
- yogadl, the flexible data layer☆74Updated last year
- Measure and visualize machine learning model performance without the usual boilerplate.☆97Updated 5 months ago
- Interactively retrieve data from sacred experiments.☆82Updated 3 weeks ago
- A tiny module for machine learning experiment orchestration☆63Updated 5 years ago
- Dashboard for sacred. Monitor and access your past machine learning experiments.☆183Updated 5 years ago
- Quick modules to turn regular Neural Networks to Bayesian Neural Networks with Dropout.☆35Updated 3 years ago
- Convenient DL serving☆72Updated 3 years ago
- Pytorch Lightning seed project with hydra☆18Updated 4 years ago
- Better, faster hyper-parameter optimization☆113Updated last year
- This library is a location of the LegacyLogger for PyTorch Lightning.☆26Updated 2 years ago
- An extension to Sacred for automated hyperparameter optimization.☆59Updated 7 years ago
- Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses☆184Updated last year
- A pytorch based classification experiments template☆46Updated 3 years ago
- A simple wrapper over `pydot` and `graphviz` which fixes some sharp edges☆63Updated 2 years ago
- Mixture Density Networks (Bishop, 1994) tutorial in JAX☆58Updated 4 years ago
- A minimal template for creating a pypi package☆49Updated 4 years ago
- A python library for stochastic variational inference and differentiable probabilistic programming☆32Updated 5 years ago
- A modular system for machinable research code☆35Updated 2 months ago
- ⏸ Parallelized hyper-param optimization with validation set, not crossval☆89Updated 2 years ago
- Lightweight interface to AWS☆47Updated 5 years ago
- A toolset for black-box hyperparameter optimisation.☆136Updated 5 years ago
- The stand-alone training engine module for the ALOHA.eu project.☆15Updated 5 years ago
- Automatic differentiation + optimization☆103Updated 5 years ago
- PyTorch implementation of the NIPS'17 paper Training Deep Networks without Learning Rates Through Coin Betting.☆37Updated 6 years ago
- A few baselines with a standard tabular model☆38Updated 4 years ago