Machine-Learning-Algorithms VS pycaret

Compare Machine-Learning-Algorithms vs pycaret and see what are their differences.

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Machine-Learning-Algorithms pycaret
1 5
25 8,428
- 1.2%
0.0 9.4
over 3 years ago 5 days ago
Jupyter Notebook Jupyter Notebook
- MIT License
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-Algorithms

Posts with mentions or reviews of Machine-Learning-Algorithms. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2020-11-01.
  • HacktoberFest Challenge Completed.
    5 projects | dev.to | 1 Nov 2020
    Now, My first PR was done. So, I was very excited. then I searched for Machine learning basic repo. made another PR there, https://github.com/aswinzz/Machine-Learning-Algorithms/pull/27

pycaret

Posts with mentions or reviews of pycaret. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-06-13.

What are some alternatives?

When comparing Machine-Learning-Algorithms and pycaret you can also consider the following projects:

tails - This is the Tails composer package for Laravel. Easily fetch designs in your Laravel application that you design inside of the Tails Site/Page Builder.

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.

awesome-machine-learning - A curated list of awesome Machine Learning frameworks, libraries and software.

pyod - A Comprehensive and Scalable Python Library for Outlier Detection (Anomaly Detection)

Face-Recognition-One-Shot-Learning- - This project is based on Siamese Neural Networks & Triplet Loss Functions

ML-For-Beginners - 12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

ML-Workspace - 🛠 All-in-one web-based IDE specialized for machine learning and data science.

imodels - Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

Twitter-sentiment-analysis - A sentiment analysis model trained with Kaggle GPU on 1.6M examples, used to make inferences on 220k tweets about Messi and draw insights from their results.

azureml-examples - Official community-driven Azure Machine Learning examples, tested with GitHub Actions.

anomalib - An anomaly detection library comprising state-of-the-art algorithms and features such as experiment management, hyper-parameter optimization, and edge inference.

CodeSearchNet - Datasets, tools, and benchmarks for representation learning of code.