mrdbourke/m1-machine-learning-test
Code for testing various M1 Chip benchmarks with TensorFlow.
This project helps data scientists and machine learning engineers set up their new Apple Silicon Mac (M1, M1 Pro, M1 Max, M1 Ultra, or M2) for machine learning workflows. It provides clear instructions and sample code to install popular data science packages like TensorFlow, Pandas, and Scikit-learn, and then benchmarks their performance. The output demonstrates that the software is correctly installed and running efficiently on your Apple device, leveraging its GPU capabilities.
536 stars. No commits in the last 6 months.
Use this if you have a new Apple Silicon Mac and want to quickly set up a stable environment for machine learning and data science, ensuring core libraries are correctly installed and utilize your hardware efficiently.
Not ideal if you are a Python developer primarily interested in web development, system scripting, or other programming tasks that do not involve machine learning or data science.
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Jupyter Notebook
License
MIT
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Last pushed
Apr 04, 2024
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