Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
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Mining URLs from dark corners of Web Archives for bug hunting/fuzzing/further probing
- parameter-finder
- parameter
- bugbounty
- content-discovery
Official repository for MOSS-Image, a 5B-parameter base DiT model with high-quality text rendering, layout generation, and efficient fine-tuning.
- controllable-generation
- foundation-models
- image-generation
- text-rendering
Automatic architecture search and hyperparameter optimization for PyTorch
- automl
- deep-learning
- tabular-data
- pytorch
Keras + Hyperopt: A very simple wrapper for convenient hyperparameter optimization
- hyperopt
- keras
- hyperparameter-optimization
rsatool can be used to calculate RSA and RSA-CRT parameters
Hyper-parameter optimization for sklearn
Hyperparameter Experiments with TensorFlow and Keras
- deep-learning
- keras
- keras-tensorflow
- hyperparameter-optimization
SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization
- bayesian-optimization
- bayesian-optimisation
- hyperparameter-optimization
- hyperparameter-tuning
An autoML framework & toolkit for machine learning on graphs.
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
Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
- python
- pytorch
- machine-learning
- deep-learning
Naive-N0.5-Flash is an open-weight 309B MoE model with 15.5B active parameters, built for coding and AI R&D.
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
Probabilistic programming framework that facilitates objective model selection for time-varying parameter models.
- time-series-analysis
- model-selection
- bayesian-inference
- anomaly-detection
Configure Python functions explicitly and safely
- hyperparameters
- machine-learning
- deep-learning
- python3
Decorator which checks whether the function is called with the correct type of parameters.
- python
- type-checking
- runtime-checking
- typechecking
Auto-optimizing a neural net (and its architecture) on the CIFAR-100 dataset. Could be easily transferred to another dataset or another classification task.
- hyperopt
- hyperparameter-optimization
- hyperparameter-tuning
- hyperparameters-optimization
Fetch and normalize parameterized URLs from the Wayback CDX API (OSINT, inspired by ParamSpider).
- bugbounty
- cdx
- cli
- kali-linux