Software Alternatives & Reviews

Scikit-learn VS PyCaret

Compare Scikit-learn VS PyCaret and see what are their differences

Scikit-learn

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

PyCaret

open source, low-code machine learning library in Python
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • PyCaret Landing page
    Landing page //
    2022-03-19

Scikit-learn

Categories
  • Data Science And Machine Learning
  • Data Science Tools
  • Python Tools
  • Software Libraries
Website scikit-learn.org  
Details $

PyCaret

Categories
  • Data Science And Machine Learning
  • Machine Learning
  • Data Dashboard
  • Data Science Tools
Website pycaret.org  
Details $

Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

  • Review - Python Machine Learning Review | Learn python for machine learning. Learn Scikit-learn.

PyCaret videos

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 Scikit-learn and PyCaret)
Data Science And Machine Learning
Data Science Tools
95 95%
5% 5
Python Tools
98 98%
2% 2
Machine Learning
0 0%
100% 100

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare Scikit-learn and PyCaret

Scikit-learn Reviews

15 data science tools to consider using in 2021
Scikit-learn is an open source machine learning library for Python that's built on the SciPy and NumPy scientific computing libraries, plus Matplotlib for plotting data. It supports both supervised and unsupervised machine learning and includes numerous algorithms and models, called estimators in scikit-learn parlance. Additionally, it provides functionality for model...

PyCaret Reviews

We have no reviews of PyCaret yet.
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Social recommendations and mentions

Based on our record, Scikit-learn seems to be a lot more popular than PyCaret. While we know about 27 links to Scikit-learn, we've tracked only 2 mentions of PyCaret. 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.

Scikit-learn mentions (27)

  • Link Prediction With node2vec in Physics Collaboration Network
    Firstly, we need a connection to Memgraph so we can get edges, split them into two parts (train set and test set). For edge splitting, we will use scikit-learn. In order to make a connection towards Memgraph, we will use gqlalchemy. - Source: dev.to / 9 months ago
  • WiFilter is a RaspAP install extended with a squidGuard proxy to filter adult content. Great solution for a family, schools and/or public access point
    The ML component is based on scikit-learn which differentiates it from purely list-based filters. It couples this with a full-featured wireless router (RaspAP) in a single device, so it fulfills the needs of a use case not entirely addressed by Pi-hole. Source: 10 months ago
  • PSA: You don't need fancy stuff to do good work.
    Finally, when it comes to building models and making predictions, Python and R have a plethora of options available. Libraries like scikit-learn, statsmodels, and TensorFlowin Python, or caret, randomForest, and xgboostin R, provide powerful machine learning algorithms and statistical models that can be applied to a wide range of problems. What's more, these libraries are open-source and have extensive... Source: 10 months ago
  • Help on using R for Machine Learning?
    Scikit-learn is a machine learning library that comes with a number of pre-built machine learning models, which can then be used as python wrappers. Source: 12 months ago
  • Machine learning with Julia - Solve Titanic competition on Kaggle and deploy trained AI model as a web service
    This is not a book, but only an article. That is why it can't cover everything and assumes that you already have some base knowledge to get the most from reading it. It is essential that you are familiar with Python machine learning and understand how to train machine learning models using Numpy, Pandas, SciKit-Learn and Matplotlib Python libraries. Also, I assume that you are familiar with machine learning... - Source: dev.to / about 1 year ago
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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: over 1 year ago
  • 👌 Zero feature engineering with Upgini+PyCaret
    PyCaret - Low-code machine learning library in Python that automates machine learning workflows. Source: over 1 year ago

What are some alternatives?

When comparing Scikit-learn and PyCaret, you can also consider the following products

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

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.

OpenCV - OpenCV (Open Source Computer Vision) is a library of programming functions for real time computer...

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

NumPy - NumPy is the fundamental package for scientific computing with Python

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