Spotify_Song_Recommender VS nni

Compare Spotify_Song_Recommender vs nni and see what are their differences.

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. (by BobbyWilt)
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Spotify_Song_Recommender nni
3 5
28 13,663
- 0.9%
0.0 6.7
almost 2 years ago 22 days ago
Jupyter Notebook Python
MIT License MIT License
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Spotify_Song_Recommender

Posts with mentions or reviews of Spotify_Song_Recommender. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning Spotify_Song_Recommender yet.
Tracking mentions began in Dec 2020.

nni

Posts with mentions or reviews of nni. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-10-04.

What are some alternatives?

When comparing Spotify_Song_Recommender and nni you can also consider the following projects:

optuna - A hyperparameter optimization framework

FLAML - A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

autogluon - AutoGluon: AutoML for Image, Text, Time Series, and Tabular Data

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

remote-jobs - A list of semi to fully remote-friendly companies (jobs) in tech.

Sklearn-genetic-opt - ML hyperparameters tuning and features selection, using evolutionary algorithms.

wtte-rnn - WTTE-RNN a framework for churn and time to event prediction