cgnorthcutt / hypoptLinks
⏸ Parallelized hyper-param optimization with validation set, not crossval
☆91Updated 2 years ago
Alternatives and similar repositories for hypopt
Users that are interested in hypopt are comparing it to the libraries listed below
Sorting:
- Measure and visualize machine learning model performance without the usual boilerplate.☆98Updated last year
- ☆26Updated 6 years ago
- Creates a learning-curve plot for Jupyter/Colab notebooks that is updated in real-time.☆177Updated 3 years ago
- Fast Differentiable Forest lib with the advantages of both decision trees and neural networks☆78Updated 3 years ago
- ☆71Updated 4 years ago
- An example of using a discriminator to correct for a difference in the distributions between the training and test data.☆67Updated 8 years ago
- A toolset for black-box hyperparameter optimisation.☆135Updated 5 years ago
- General Interpretability Package☆58Updated 2 years ago
- Training time estimation for scikit-learn algorithms☆124Updated 4 years ago
- Better, faster hyper-parameter optimization☆113Updated last year
- A simple, extensible library for developing AutoML systems☆175Updated 2 years ago
- An AutoML pipeline selection system to quickly select a promising pipeline for a new dataset.☆84Updated 3 years ago
- NeuralPy: A Keras like deep learning library works on top of PyTorch☆79Updated last year
- An automatic ML model optimization tool.☆200Updated 2 years ago
- Provides a systematic and extensible way to build, train, evaluate, and tune deep learning models using PyTorch.☆94Updated last year
- Supporting code for the paper "Finding Influential Training Samples for Gradient Boosted Decision Trees"☆68Updated last year
- fastai V2 implementation of Timeseries classification papers.☆241Updated 2 years ago
- Practical Deep Learning resources for Time series analysis and forecasting☆85Updated 4 years ago
- A Python package for unwrapping ReLU DNNs☆70Updated last year
- A scikit-learn compatible implementation of hyperband☆76Updated 5 years ago
- Hyperparameter optimization that enables researchers to experiment, visualize, and scale quickly.☆341Updated 4 years ago
- Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses☆190Updated last year
- A python script for a PyTorch feed forward neural network for tabular data using categorical embeddings.☆67Updated 5 years ago
- python library implementing ensemble methods for regression, classification and visualisation tools including Voronoi tesselations.☆125Updated 5 years ago
- A clustering algorithm that automatically determines the number of clusters and works without hyperparameter fine-tuning.☆218Updated 4 years ago
- Keras/TF implementation of AdamW, SGDW, NadamW, Warm Restarts, and Learning Rate multipliers☆169Updated 3 years ago
- Code examples for my Interpretable Machine Learning Blog Series☆57Updated 5 years ago
- Experimental Gradient Boosting Machines in Python with numba.☆185Updated 6 years ago
- Preparing continuous features for neural networks with GaussRank☆45Updated 7 years ago
- To Trust Or Not To Trust A Classifier. A measure of uncertainty for any trained (possibly black-box) classifier which is more effective t…☆177Updated 2 years ago