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Scikit-learn VS MLJAR

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

LibHunt
LibHunt tracks mentions of software libraries on relevant social networks. Based on that data, you can find the most popular projects and their alternatives. featured
Contents:
  1. » Base Details
  2. » Videos
  3. » Reviews
  4. » Alternatives

Scikit-learn logo Scikit-learn

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

MLJAR logo MLJAR

MLJAR is a predictive analytics platform that facilitates machine learning algorithms search and tuning.
  • Scikit-learn Landing page
    Landing page //
    2022-05-06
  • MLJAR Landing page
    Landing page //
    2023-06-14

Scikit-learn videos

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Learning Scikit-Learn (AI Adventures)

More videos:

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

MLJAR videos

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Category Popularity

0-100% (relative to Scikit-learn and MLJAR)

Scikit-learn

MLJAR

Data Science And Machine Learning
97 97%
Data Science And Machine Learning
3% 3
Data Science Tools
97 97%
Data Science Tools
3% 3
Python Tools
97 97%
Python Tools
3% 3
Data Dashboard
89 89%
Data Dashboard
11% 11

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 MLJAR

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...
Source: searchbusinessanalytics.techtarget.com

MLJAR Reviews

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Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than MLJAR. It has been mentiond 28 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.

Scikit-learn mentions (28)

  • How to Build a Logistic Regression Model: A Spam-filter Tutorial
    Online Courses: Coursera: "Machine Learning" by Andrew Ng EdX: "Introduction to Machine Learning" by MIT Tutorials: Scikit-learn documentation: https://scikit-learn.org/ Kaggle Learn: https://www.kaggle.com/learn Books: "Hands-On Machine Learning with Scikit-Learn, Keras & TensorFlow" by Aurélien Géron "The Elements of Statistical Learning" by Trevor Hastie, Robert Tibshirani, and Jerome Friedman By... - Source: dev.to / 2 months ago
  • 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 / 11 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: 12 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: about 1 year 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: about 1 year ago
View more

MLJAR mentions (3)

  • [P] Build data web apps in Jupyter Notebook with Python only
    Sure, at the bottom of our website you can subscribe for newsletter. Source: about 1 year ago
  • Data Science and full-stack-web development
    In my case, I had experience in DS and software engineering. It gives me ability to start a company that works on Data Science tools. Source: about 2 years ago
  • [D] Bring your own data AI SaaS service for non-programmers?
    Instead, we started to work on desktop application that will allow to create python notebooks with no-code GUI (https://github.com/mljar/studio some screenshots on our website ). Source: over 2 years ago

What are some alternatives?

When comparing Scikit-learn and MLJAR, 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.

Google Cloud Machine Learning - Google Cloud Machine Learning is a service that enables user to easily build machine learning models, that work on any type of data, of any size.

OpenCV - OpenCV is the world's biggest computer vision library

Amazon Machine Learning - Machine learning made easy for developers of any skill level

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

Teachable Machine - Easily create machine learning models for your apps, no coding required.

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