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A hyperparameter optimization framework
The AI developer platform. Use Weights & Biases to train and fine-tune models, and manage models from experimentation to production.
- machine-learning
- experiment-track
- deep-learning
- keras
Fast and Accurate ML in 3 Lines of Code
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Automated Machine Learning with scikit-learn
- automl
- scikit-learn
- automated-machine-learning
- hyperparameter-optimization
Distributed Asynchronous Hyperparameter Optimization in Python
- hacktoberfest
AI Infra / AI Orchestration / AI Control Plane
Determined is an open-source machine learning platform that simplifies distributed training, hyperparameter tuning, experiment tracking, and resource management. Works with PyTorch and TensorFlow.
- deep-learning
- machine-learning
- ml-platform
- ml-infrastructure
Automatic architecture search and hyperparameter optimization for PyTorch
- automl
- deep-learning
- tabular-data
- pytorch
2-2000x faster ML algos, 50% less memory usage, works on all hardware - new and old.
Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.
- kv-cache
- llm-inference
- local-llm
- quantization
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
- hyperopt
- keras
- hyperparameter-optimization
Machine Learning in R
- machine-learning
- data-science
- tuning
- cran
Hyper-parameter optimization for sklearn
Hyperparameter Experiments with TensorFlow and Keras
- deep-learning
- keras
- keras-tensorflow
- hyperparameter-optimization
Library for Fast and Flexible Human Pose Estimation
- tensorlayer
- tensorflow
- openpose
- pose-estimation
An autoML framework & toolkit for machine learning on graphs.
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
Rebuild a reference video as an editable HyperFrames project, compare the match against the original, and export an MP4.
- hyperframes
- motion-graphics
- python
- video
Cleora AI is a general-purpose open-source model for efficient, scalable learning of stable and inductive entity embeddings for heterogeneous relational data. Created by Synerise.com team.
- ai
- graphs
- synerise
- embeddings
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
This extension transforms the Gemini CLI into "Pickle Rick," a hyper-intelligent, arrogant, yet extremely competent engineering persona. It enforces a rigid, iterative software development lifecycle through continuous AI agent loops. Emphasizing "God Mode" coding practices and a disdain for
- ai
- gemini
- gemini-cli
- gemini-cli-extensions
Hyperparameter optimization and feature selection for scikit-learn using evolutionary algorithms. A modern alternative to GridSearchCV and RandomizedSearchCV.