nni
FLAML
Our great sponsors
nni | FLAML | |
---|---|---|
5 | 9 | |
13,663 | 3,618 | |
0.9% | 2.8% | |
6.7 | 8.3 | |
22 days ago | 6 days ago | |
Python | Jupyter Notebook | |
MIT License | 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.
nni
-
Automated Machine Learning (AutoML) - 9 Different Ways with Microsoft AI
For a complete tutorial, navigate to this Jupyter Notebook: https://github.com/microsoft/nni/blob/master/examples/notebooks/tabular_data_classification_in_AML.ipynb
-
[D] Efficient ways of choosing number of layers/neurons in a neural network
optuna, hyperopt, nni, plenty of less-known tools too.
-
Top 10 Developer Trends, Sun Oct 18 2020
microsoft / nni
FLAML
-
Elevate Your Python Skills: Machine Learning Packages That Transformed My Journey as ML Engineer
4. FLAML
- Show HN: AutoML Python Package for Tabular Data with Automatic Documentation
-
what is the future of ML.NET?
Improved AutoML - Again, with collaboration from Microsoft Research, we used FLAML to update our existing AutoML solutions. What does this mean for you? You're using the latest techniques but all you need is a problem to solve and some data to get started.
-
Automated Machine Learning (AutoML) - 9 Different Ways with Microsoft AI
For a complete tutorial, navigate to this Jupyter Notebook: https://github.com/microsoft/FLAML/blob/main/notebook/flaml_automl.ipynb
What are some alternatives?
optuna - A hyperparameter optimization framework
autogluon - AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data
H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.
ML-For-Beginners - 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all
AutoML - This is a collection of our NAS and Vision Transformer work. [Moved to: https://github.com/microsoft/Cream]
hyperopt - Distributed Asynchronous Hyperparameter Optimization in Python
automlbenchmark - OpenML AutoML Benchmarking Framework
archai - Accelerate your Neural Architecture Search (NAS) through fast, reproducible and modular research.
tsflex - Flexible time series feature extraction & processing
LightAutoML - LAMA - automatic model creation framework
Made-With-ML - Learn how to design, develop, deploy and iterate on production-grade ML applications.