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Caravel VS Scikit-learn

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

Caravel logo Caravel

Visual, intuitive, and interactive data exploration platform

Scikit-learn logo Scikit-learn

scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.
  • Caravel Landing page
    Landing page //
    2023-10-18
  • Scikit-learn Landing page
    Landing page //
    2022-05-06

Caravel videos

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Scikit-learn videos

Learning Scikit-Learn (AI Adventures)

More videos:

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

Category Popularity

0-100% (relative to Caravel and Scikit-learn)
Data Dashboard
15 15%
85% 85
Data Science And Machine Learning
Data Visualization
100 100%
0% 0
Data Science Tools
0 0%
100% 100

User comments

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Reviews

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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...

Social recommendations and mentions

Based on our record, Scikit-learn should be more popular than Caravel. It has been mentiond 29 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.

Caravel mentions (10)

  • A library for querying APIs and files using SQL
    Also, many tools only talk SQL. Shillelagh was developed for Apache Superset, a powerful open source business intelligence web application, and allows it to query an infinitude of new data sources without having to change a single line of code in Superset. Source: almost 2 years ago
  • Easy way of copying web data to excel.
    I'm adding this to Apache Superset today! Source: almost 2 years ago
  • Apache Superset and Azure - multi-container application deployment
    I also like to do some data analysis on the side and recently ran across Apache Superset which describes itself as a "modern data exploration and data visualization platform". Coincidentally, Superset has a lot of Python code and can be deployed in containers (nine of them at current count!). - Source: dev.to / about 2 years ago
  • Building a metrics dashboard with Superset and Cube
    Please don't hesitate to like and bookmark this post, write a comment, and give a star to Cube and Superset on GitHub. I hope these tools would be a part of your toolkit when you decide to build a metrics store and a business intelligence application on top of it. - Source: dev.to / over 2 years ago
  • When You Merge Pull Requests You Lose Knowledge
    Discussion by kgabryje at apache / superset “feat(native-filters): add search all filter options #14710“. - Source: dev.to / almost 3 years ago
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Scikit-learn mentions (29)

  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize data splitting tools in libraries like Scikit-learn to partition your dataset. Make sure the split mirrors the real-world distribution of your data to avoid biased evaluations. - Source: dev.to / 6 days ago
  • 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 / 4 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 / about 1 year 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: about 1 year 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
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What are some alternatives?

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

Mage AI - Open-source data pipeline tool for transforming and integrating data.

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

Aha! Visual Chart Tool - Create beautiful product roadmap visualizations

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

Apache Superset - modern, enterprise-ready business intelligence web application

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