Try Google Colab
Google Colab is a free cloud-based platform that allows you to write and execute Python code in a notebook format.
- Free access to GPUs and TPUs
- No installation required
- Collaboration made easy
- Integration with Google Drive
To start using Google Colab, simply visit the
Colab Website and sign in with your Google account. From there, you can create a new notebook or upload an existing one. To utilize GPU resources, navigate to the "Runtime" menu, select "Change runtime type" and choose GPU or TPU as your hardware accelerator.
Try MacBook Air - 16 Neural Engines
If you prefer working on a local machine, the MacBook Air with Apple’s M1, M2, or M3 chip presents an impressive alternative for running machine learning tasks. Working with Apple’s ecosystem, the new integration of Metal Performance Shaders (MPS) with PyTorch brings significant improvements to training acceleration. Apple's Metal is a low-level, high-performance graphics API that lets programmers connect directly to the GPU. MPS are a special group of highly optimized compute kernels in the Metal framework that speed up tasks that need a lot of computing power, like machine learning. The MPS framework is designed to work with Apple's GPUs, which allows you to fine-tune speed for image processing, machine learning tasks, and other scientific computing tasks.
To use MPS in your local environment, simply use the following line of code:
device = torch.device("mps" if torch.backends.mps.is_built() else "CPU")
Now You’re Ready to Code!