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Kaggle is a website that hosts machine learning and data science competitions, datasets, and tools. You can join events, learn from tutorials, and collaborate with other data scientists on Kaggle.
- Datasets
Explore all public datasets. Download Open Datasets on 1000s...
- Sign In
Sign In - Kaggle: Your Machine Learning and Data Science...
- Python
Python - Kaggle: Your Machine Learning and Data Science...
- Learn
Explore these curated collections of high-quality learning...
- Code Code
Code Code - Kaggle: Your Machine Learning and Data Science...
- Kaggle Competitions
Kaggle Competitions - Kaggle: Your Machine Learning and Data...
- Comment Discussions
Comment Discussions - Kaggle: Your Machine Learning and Data...
- Tenancy Models
Explore machine learning code authored by the Kaggle...
- Datasets
Kaggle is a platform for exploring, analyzing, and sharing quality data. Find datasets from various domains, such as computer science, education, sports, health, software, food, and travel, or create and share your own projects.
Explore and download thousands of open datasets on Kaggle , the home of data science and machine learning.
Kaggle is a data science competition platform and online community for data scientists and machine learning practitioners under Google LLC. Kaggle enables users to find and publish datasets, explore and build models in a web-based data science environment, work with other data scientists and machine learning engineers, and enter competitions to ...
Kaggle is the world's largest community of data scientists. Watch videos to learn how to use Kaggle's platform, compete in competitions, collaborate with others, and access free code and data.
Oct 16, 2018 · In this video, Kaggle Data Scientist Rachael gives you a quick tour of the Kaggle platform, including Kernels (our hosted, in-browser data science coding environment), Datasets and Learn ...
- 2 min
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- Kaggle
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Sep 21, 2023 · Kaggle is a Google-owned platform that hosts data science challenges and offers datasets, courses and forums. Learn how to compete in Kaggle competitions, what benefits they offer and what alternatives exist.
