Introduction to Pytorch Tutorial and Resources at Boston University
Explore the comprehensive tutorial and resources for Pytorch at Boston University, including downloading Jupyter notebooks, using SCC OnDemand, and tutorial feedback survey. Enhance your knowledge on Pytorch with guidance from experts.
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Introduction to Pytorch Scott Ladenheim, PhD help@rcs.bu.edu
Please check your name on the attendance sheet
The course materials can be found at: https://rcs.bu.edu/examples/machine_learning/pytorch/ If you have not already done so, download the Jupyter notebook file IntroductionToPytorch.ipynb On the SCC copy the notebook to your home directory using this terminal command: Course materials cp /project/scv/examples/machine_learning/pytorch/IntroductionToPytrochCPU.ipynb ~ You can also download the slides Slides-IntroductionToPytorch.pptx
Jupyter notebooks using SCC OnDemand If you have an SCC account Open a web browser Navigate to scc-ondemand.bu.edu Login using BU id and password Select Jupyter Notebook from the Interactive Apps tab Fill in the request with the following information Modules: miniconda/23.1.0 academic-ml Pre-Launch Command: conda activate spring-2024-pyt Number of hours: 2 Number of cores: 1 Click the blue Launch button
Jupyter notebooks using SCC OnDemand If you do NOT have an SCC account Open a web browser Navigate to: scc-ondemand-tutorial.bu.edu Login using ID tuta# (# is the number on your desk) Password is LittleMartha# (# is the number on your desk) Select Jupyter Notebook from the Interactive Apps tab Fill in the request with the following information Modules: miniconda/23.1.0 academic-ml Pre-Launch Command: conda activate spring-2024-pyt Number of hours: 2 Number of cores: 1 Click the blue Launch button
Tutorial outline Pytorch neural network CPU vs GPU Autograd
http://rcs.bu.edu/evalNavigate to http://rcs.bu.edu/eval After the tutorial Tutorial feedback survey
