Shypd.aiThe largest open index of AI toolsm1-machine-learning-test provides code for benchmarking M1 chip performance with TensorFlow. It includes setup instructions for Apple Silicon Macs to run machine learning and data science packages.
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m1-machine-learning-test is a GitHub repository offering code and detailed instructions for benchmarking the performance of Apple's M1, M1 Pro, M1 Max, M1 Ultra, and M2 chips when running machine learning tasks with TensorFlow. The repository includes sample code for various experiments, such as training a TinyVGG model on CIFAR10, an EfficientNetB0 feature extractor on Food101, and a RandomForestClassifier on the California Housing dataset. It provides comprehensive guides for setting up a TensorFlow environment on Apple Silicon using Miniforge, installing necessary dependencies like tensorflow-macos and tensorflow-metal for GPU acceleration, and common data science packages like Jupyter, pandas, numpy, matplotlib, and scikit-learn. This resource is ideal for developers and data scientists looking to optimize and test machine learning workflows on Apple's hardware.
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