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  1. Kaggle is the world’s largest data science community with powerful tools and resources to help you achieve your data science goals.

    • Datasets

      Datasets - Kaggle: Your Machine Learning and Data Science...

    • Code

      Code - Kaggle: Your Machine Learning and Data Science...

    • Learn

      Learn - Kaggle: Your Machine Learning and Data Science...

    • Sign In

      Kaggle is the world’s largest data science community with...

    • Competitions

      Kaggle is the world’s largest data science community with...

    • Download

      Welcome to Kaggle! Join Kaggle, the world's largest...

  2. Enhance your experience with the desktop app for Kaggle on WebCatalog Desktop for Mac, Windows, Linux. Run apps in distraction-free windows with many enhancements. Manage and switch between multiple accounts and apps easily without switching browsers.

  3. Welcome to Kaggle! Join Kaggle, the world's largest community of data scientists. Find datasets and code as well as access to compute on our platform at no cost.

  4. Mar 10, 2017 · Kaggle is a community and site for hosting machine learning competitions. Competitive machine learning can be a great way to develop and practice your skills, as well as demonstrate your capabilities.

  5. A place to ask questions and get advice from the thousands of data scientists in the Kaggle community. There are six general site Discussion Forums: Kaggle Forum: Events and topics specific to the Kaggle community. Getting Started: The first stop for questions and discussion for new Kagglers.

  6. Oct 26, 2021 · Kaggle is now so huge that it can be overwhelming to understand. It is common to not know about using it to learn data science. In this article, I am going to explain about getting started with Kaggle to learn data science. Learn the basics. Kaggle has many short courses on various data science-related topics.

  7. Mar 8, 2017 · Kaggle is an online community platform for data scientists and machine learning enthusiasts. Kaggle allows users to collaborate with other users, find and publish datasets, use GPU integrated notebooks, and compete with other data scientists to solve data science challenges.