dmatrix2np
Hyperactive
| dmatrix2np | Hyperactive | |
|---|---|---|
| 2 | 8 | |
| 17 | 490 | |
| - | - | |
| 0.0 | 7.7 | |
| over 2 years ago | 5 months ago | |
| Python | Python | |
| GNU General Public License v3.0 only | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
dmatrix2np
-
You can convert from DMatrix to NumPy array!
It's open-source so you can take a look at the code here: https://github.com/aporia-ai/dmatrix2np
Hyperactive
- Hyperactive Version 4.5 Released
- Hyperactive: An optimization and data collection toolbox for AutoML
- Hyperactive: Optimize computationally expensive models with powerful algorithms
- Show HN: Hyperactive – A highly versatile AutoML Toolbox
-
Hyperactive – Easy Neural Architecture Search for Deep Learning in Python
Check out the Neural Architecture Search Tutorial here: https://nbviewer.jupyter.org/github/SimonBlanke/hyperactive-...
Neural Architecture Search is just one of many optimization applications you can work on with Hyperactive. Check out the examples in the official github repository: https://github.com/SimonBlanke/Hyperactive/tree/master/examp...
-
Gradient-Free-Optimizers A collection of modern optimization methods in Python
Gradient-Free-Optimizers is a lightweight optimization package that serves as a backend for Hyperactive: https://github.com/SimonBlanke/Hyperactive
Hyperactive can do parallel computing with multiprocessing or joblib, or a custom wrapper-function.
What are some alternatives?
m2cgen - Transform ML models into a native code (Java, C, Python, Go, JavaScript, Visual Basic, C#, R, PowerShell, PHP, Dart, Haskell, Ruby, F#, Rust) with zero dependencies
mango - Parallel Hyperparameter Tuning in Python
mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
pybobyqa - Python-based Derivative-Free Optimization with Bound Constraints
neptune-client - 📘 The MLOps stack component for experiment tracking
opytimizer - 🐦 Opytimizer is a Python library consisting of meta-heuristic optimization algorithms.
mljar-supervised - Python package for AutoML on Tabular Data with Feature Engineering, Hyper-Parameters Tuning, Explanations and Automatic Documentation
OpenMetadata - Open Standard for Metadata. A Single place to Discover, Collaborate and Get your data right.
optuna-examples - Examples for https://github.com/optuna/optuna
optimization-tutorial - Tutorials for the optimization techniques used in Gradient-Free-Optimizers and Hyperactive.
anovos - Anovos - An Open Source Library for Scalable feature engineering Using Apache-Spark
Auto_ViML - Automatically Build Multiple ML Models with a Single Line of Code. Created by Ram Seshadri. Collaborators Welcome. Permission Granted upon Request.