machine_learning_basics VS mango

Compare machine_learning_basics vs mango and see what are their differences.

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machine_learning_basics mango
5 -
4,205 310
- 1.6%
0.0 5.8
3 months ago about 2 months ago
Jupyter Notebook Jupyter Notebook
MIT License Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
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.

machine_learning_basics

Posts with mentions or reviews of machine_learning_basics. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-01-29.

mango

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

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

What are some alternatives?

When comparing machine_learning_basics and mango you can also consider the following projects:

Financial-Models-Numerical-Methods - Collection of notebooks about quantitative finance, with interactive python code.

Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.

100-Days-Of-ML-Code - 100 Days of ML Coding

vizier - Python-based research interface for blackbox and hyperparameter optimization, based on the internal Google Vizier Service.

borb-google-colab-examples - This repository contains some examples of using borb in google colab. These examples enable you to try out the features of borb without installing it on your system. They also ensure the system requirements and imports are all taken care of.

neural-tangents - Fast and Easy Infinite Neural Networks in Python

trulens - Evaluation and Tracking for LLM Experiments

Bayesian-Optimization-in-FSharp - Bayesian Optimization via Gaussian Processes in F#

rmi - A learned index structure

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.

PyImpetus - PyImpetus is a Markov Blanket based feature subset selection algorithm that considers features both separately and together as a group in order to provide not just the best set of features but also the best combination of features

nni - An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.