Setup Mac for Machine Learning with PyTorch in 11 minutes (works for all M1, M2)

Daniel Bourke · Beginner ·📰 AI News & Updates ·3y ago
Skills: ML Pipelines70%
Setup your Apple M1 or M2 (Normal, Pro, Max or Ultra) Mac for data science and machine learning with PyTorch. Get the code on GitHub - https://github.com/mrdbourke/pytorch-apple-silicon PyTorch on Mac announcement blog post - https://pytorch.org/blog/introducing-accelerated-pytorch-training-on-mac/ Learn PyTorch - https://learnpytorch.io Setup Apple M1 for TensorFlow - https://youtu.be/_1CaUOHhI6U Other links: Learn ML (beginner-friendly courses I teach) - https://www.mrdbourke.com/ml-courses/ ML courses/books I recommend - https://www.mrdbourke.com/ml-resources/ Read my novel Charlie Walks - https://www.charliewalks.com Connect elsewhere: Web - https://dbourke.link/web Twitter - https://www.twitter.com/mrdbourke Twitch - https://www.twitch.tv/mrdbourke ArXiv channel (past streams) - https://dbourke.link/archive-channel Get email updates on my work - https://dbourke.link/newsletter Timestamps: 0:00 - Intro and what we’re covering 1:00 - Open Terminal 1:30 - Requirements 2:22 - 1. Download and install Homebrew 3:51 - 2. Download Miniforge3 4:35 - 3. Install Miniforge3 to get access to Conda 6:10 - 4. Restart Terminal 6:25 - 5. Create a directory to hold the environment/test PyTorch 6:40 - 6. Create a Conda environment and activate it 7:32 - 7. Install PyTorch for Mac 9:01 - 8. Install common data science packages (Jupyter, NumPy, pandas etc) 9:35 - 9. Start a Jupyter Notebook server and create a new notebook 10:00 - 10. Running import code and testing whether PyTorch has access to GPU 11:05 - 11. Seeing if PyTorch can send a tensor to the MPS device
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Chapters (14)

Intro and what we’re covering
1:00 Open Terminal
1:30 Requirements
2:22 1. Download and install Homebrew
3:51 2. Download Miniforge3
4:35 3. Install Miniforge3 to get access to Conda
6:10 4. Restart Terminal
6:25 5. Create a directory to hold the environment/test PyTorch
6:40 6. Create a Conda environment and activate it
7:32 7. Install PyTorch for Mac
9:01 8. Install common data science packages (Jupyter, NumPy, pandas etc)
9:35 9. Start a Jupyter Notebook server and create a new notebook
10:00 10. Running import code and testing whether PyTorch has access to GPU
11:05 11. Seeing if PyTorch can send a tensor to the MPS device
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