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CatBoost VS PyCaret

Compare CatBoost VS PyCaret and see what are their differences

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CatBoost logo CatBoost

CatBoost - state-of-the-art open-source gradient boosting library with categorical features support, https://catboost.yandex/ #catboost

PyCaret logo PyCaret

open source, low-code machine learning library in Python
  • CatBoost Landing page
    Landing page //
    2021-10-16
  • PyCaret Landing page
    Landing page //
    2022-03-19

CatBoost videos

+ Add

[Paper Review]Catboost: Unbiased Boosting with Categorical Features

More videos:

  • Review - 04-9: Ensemble Learning - CatBoost (앙상블 기법 - CatBoost)
  • Review - Free Udemy Course - CatBoost vs XGBoost - Classification and Regression Modeling with Python

PyCaret videos

+ Add

Quick tour of PyCaret (a low-code machine learning library in Python)

More videos:

  • Review - Automate Anomaly Detection Using Pycaret -Data Science And Machine Learning
  • Review - Machine Learning in Power BI with PyCaret- Podcast With Moez- Author Of Pycaret

Category Popularity

0-100% (relative to CatBoost and PyCaret)

CatBoost

PyCaret

Data Science And Machine Learning
35 35%
Data Science And Machine Learning
65% 65
Data Science Tools
36 36%
Data Science Tools
64% 64
Machine Learning
38 38%
Machine Learning
62% 62
Python Tools
49 49%
Python Tools
51% 51

User comments

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Social recommendations and mentions

Based on our record, CatBoost should be more popular than PyCaret. It has been mentiond 4 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

CatBoost mentions (4)

  • What's New with AWS: Amazon SageMaker built-in algorithms now provides four new Tabular Data Modeling Algorithms
    CatBoost is another popular and high-performance open-source implementation of the Gradient Boosting Decision Tree (GBDT). To learn how to use this algorithm, please see example notebooks for Classification and Regression. - Source: dev.to / almost 2 years ago
  • Writing the fastest GBDT libary in Rust
    Here are our benchmarks on training time comparing Tangram's Gradient Boosted Decision Tree Library to LightGBM, XGBoost, CatBoost, and sklearn. - Source: dev.to / over 2 years ago
  • Data Science toolset summary from 2021
    Catboost - CatBoost is an open-source software library developed by Yandex. It provides a gradient boosting framework which attempts to solve for Categorical features using a permutation driven alternative compared to the classical algorithm. Link - https://catboost.ai/. - Source: dev.to / over 2 years ago
  • CatBoost Quickstart — ML Classification
    CatBoost is an open source algorithm based on gradient boosted decision trees. It supports numerical, categorical and text features. Check out the docs. - Source: dev.to / about 3 years ago

PyCaret mentions (2)

  • How to know what algorithm to apply? THEORY
    Anyway, nowadays there are autoML python packages that once you defined what type of problem you have to solve (e.g. regression, classification) , they automatically train differnt models at once and calculate the best performance. I used a lot the library Pycaret . Source: almost 2 years ago
  • 👌 Zero feature engineering with Upgini+PyCaret
    PyCaret - Low-code machine learning library in Python that automates machine learning workflows. Source: almost 2 years ago

What are some alternatives?

When comparing CatBoost and PyCaret, you can also consider the following products

TensorFlow - TensorFlow is an open-source machine learning framework designed and published by Google. It tracks data flow graphs over time. Nodes in the data flow graphs represent machine learning algorithms. Read more about TensorFlow.

PyTorch - Open source deep learning platform that provides a seamless path from research prototyping to...

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Keras - Keras is a minimalist, modular neural networks library, written in Python and capable of running on top of either TensorFlow or Theano.

Deeplearning4j - Deeplearning4j is an open-source, distributed deep-learning library written for Java and Scala.

mlpack - mlpack is a scalable machine learning library, written in C++.

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