Bayesian-Optimization-in-FSharp
Spotify_Song_Recommender
Bayesian-Optimization-in-FSharp | Spotify_Song_Recommender | |
---|---|---|
1 | 3 | |
5 | 28 | |
- | - | |
10.0 | 0.0 | |
over 1 year ago | almost 2 years ago | |
Jupyter Notebook | Jupyter Notebook | |
- | 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.
Bayesian-Optimization-in-FSharp
Spotify_Song_Recommender
-
Spotify Song Recommender that uses Data Science Modeling
You can find the github project Here. To run the code, download the notebook file (.ipynb) and load it in google colab. Once you have it loaded, there are step by step instructions in the notebook. The code is pretty easy to run and just requires some link copy and pasting, so I would so programming experience is not required.
- Spotify Song Recommender
What are some alternatives?
BayesianOptimization - A Python implementation of global optimization with gaussian processes.
Machine-Learning-Specialization-Coursera - Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
neural-tangents - Fast and Easy Infinite Neural Networks in Python
handson-ml - ⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.
mango - Parallel Hyperparameter Tuning 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.
StravaKudos - :running: :dart: Predicting Strava Kudos on my own activities using the given activity's attributes.
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.
feature-engineering-tutorials - Data Science Feature Engineering and Selection Tutorials
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.