mango
Bayesian-Optimization-in-FSharp
mango | Bayesian-Optimization-in-FSharp | |
---|---|---|
- | 1 | |
310 | 5 | |
1.0% | - | |
5.8 | 10.0 | |
about 2 months ago | over 1 year ago | |
Jupyter Notebook | Jupyter Notebook | |
Apache License 2.0 | - |
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.
mango
We haven't tracked posts mentioning mango yet.
Tracking mentions began in Dec 2020.
Bayesian-Optimization-in-FSharp
What are some alternatives?
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
BayesianOptimization - A Python implementation of global optimization with gaussian processes.
machine_learning_basics - Plain python implementations of basic machine learning algorithms
Spotify_Song_Recommender - This project leverages spotify's api and provided user playlists to create and tune a neural network model that generates song recommendations based off of song data in provided playlists.
vizier - Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.
neural-tangents - Fast and Easy Infinite Neural Networks in Python
d2l-en - Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Intrusion-Detection-System-Using-Machine-Learning - Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)
nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
coursera-deep-learning-specialization - Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization; (iii) Structuring Machine Learning Projects; (iv) Convolutional Neural Networks; (v) Sequence Models