Automatic architecture search and hyperparameter optimization for PyTorch
- automl
- deep-learning
- tabular-data
- pytorch
Repository Index
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Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
- hyperopt
- keras
- hyperparameter-optimization
ILGPU JIT Compiler for high-performance .Net GPU programs
Machine Learning in R
- machine-learning
- data-science
- tuning
- cran
Hyperparameter Experiments with TensorFlow and Keras
- deep-learning
- keras
- keras-tensorflow
- hyperparameter-optimization
1M param OCR model - runs on CPU, 15x faster than tesseract, close to 1B+ param models in accuracy
:truck: Agile Data Preparation Workflows made easy with Pandas, Dask, cuDF, Dask-cuDF, Vaex and PySpark
C++-based high-performance parallel environment execution engine (vectorized env) for general RL environments.
- reinforcement-learning
- parallel-processing
- cpp17
- pybind11
One advanced and mature open-source MPP (Massively Parallel Processing) database. Open source alternative to Greenplum Database.
- database
- data-analysis
- data-warehouse
- olap
Native speech-to-text for Linux - Fast, accurate, private, and hackable system-wide dictation
:chart_with_upwards_trend: Adaptive: parallel active learning of mathematical functions
- adaptive-learning
- machine-learning
- python
- live-plots
GRASS - free and open-source geospatial processing engine
- grass-gis
- geospatial
- geospatial-analysis
- raster
An autoML framework & toolkit for machine learning on graphs.
:four_leaf_clover: Evolutionary optimization library for Go (genetic algorithm, partical swarm optimization, differential evolution)
Pythonic tool for orchestrating machine-learning/high performance/quantum-computing workflows in heterogeneous compute environments.
- hpc
- workflow
- workflow-automation
- workflow-management
Light-weight camera LiDAR calibration package for ROS using OpenCV and PCL (PnP + LM optimization)
- ros-kinetic
- camera-calibration
- lidar-camera-calibration
- point-cloud
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.
- pipeline
- pipeline-framework
- machine-learning
- deep-learning
A Python platform to perform parallel computations of optimisation tasks (global and local) via the asynchronous generalized island model.
- optimization
- optimization-algorithms
- optimization-methods
- optimization-problem
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
Exascale multiphase flow solver — 2025 Gordon Bell Prize Finalist | 200T grid points on 43K+ GPUs
- gpu
- exascale
- cfd
- fortran
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.
Bayesian Optimization using GPflow
- gpflow
- bayesian-optimization
- machine-learning
- hyperparameter-optimization
Legend of Elya — N64 game with a real 6.36M-parameter ternary transformer on the VR4300 MIPS III CPU. Zelda-style dungeon, AI NPCs, byte-level inference at 1.23 tok/s scalar / 2.19 tok/s on the RSP overlay (measured under ares, never on silicon). Built with libdragon.
Configure Python functions explicitly and safely
- hyperparameters
- machine-learning
- deep-learning
- python3