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data-science-ipython-notebooks
donnemartin/data-science-ipython-notebooks
Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
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Python
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Updated: Today
📋 Project at a Glance
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What's this?A , built with Python open-source project in the Plugins, MCP & Skills category, core strengths: aws/big-data
Who made it?Maintained by donnemartin team, 29.3K⭐ on GitHub, #31 out of 2373 in Plugins, MCP & Skills
Why does it exist?In the Plugins, MCP & Skills space, aws workflows faced efficiency bottlenecks. data-science-ipython-notebooks was built by donnemartin to address these big-data challenges.
What can it do?Key use cases: caffe, data-science, deep-learning
How to install with AI?Use an AI coding assistant (Claude Code, Cursor, Copilot) to automatically set up pip dependencies and virtual env. Follow the README — the AI handles the rest.
🔗 github.com/donnemartin/data-science-ipython-notebooks
🔗 github.com/donnemartin/data-science-ipython-notebooks
Topics
awsbig-datacaffedata-sciencedeep-learninghadoopkagglekerasmachine-learningmapreducematplotlibnumpypandaspythonscikit-learnscipysparktensorflowtheano