Introduction to ML with PyTorch
Instructor:
Marie-Helene Burle (WestGrid)
Length:
2 days
Level:
Beginner
Prerequisites:
Familiarity with Python*
Goal:
Clarify concepts of machine learning and guide you through the first steps with PyTorch
Program:
We will meet during the Zoom sessions
You will go over the material in Readings, Videos, and Practices on your own
Going over the self-directed sections prior to our meetings is necessary to be able to follow
Time zone:
Pacific Daylight Time (UTC-07:00)
July 9
9–9:30am
Zoom
Introduction to the WestGrid Summer school PyTorch course
In this session, I will introduce the course, explain what you have to do before our next meeting, and give you a username for the training cluster.
In this session, I will introduce the course, explain what you have to do before our next meeting, and give you a username for the training cluster.
Our Zoom cap is 100 people and, for this course, we are using a cluster with 100 user names. There are however many more than 100 people on the waitlist. We are doing a repeat of this course to give some of you another chance to attend, but unfortunately, not everybody will be able to join if we reach our cap.
A username for the cluster will only be given to those joining this opening session.
Practice
(Optional)
Reading
Reading
2–3:30pm
(Debug)
Issues accessing and setting up the training cluster
This session is not part of the actual course. Please only sign up for it if you have followed the instructions on Training cluster setup but are having issues accessing our training cluster or installing the required Python packages in a virtual environment.
This session is not part of the actual course. Please only sign up for it if you have followed the instructions on Training cluster setup but are having issues accessing our training cluster or installing the required Python packages in a virtual environment.
Practice
Video
Video
Practice
July 10
9–11am
Zoom
Our first neural network
In this session, we will put everything you learnt yesterday together to write our first neural network.
In this session, we will put everything you learnt yesterday together to write our first neural network.
External resources
PyTorch documentation:
PyTorch website
PyTorch documentation
PyTorch tutorials
PyTorch online courses
PyTorch examples
Getting help with PyTorch:
PyTorch Discourse forum
Open-access ML preprints:
Arxiv Sanity Preserver by Andrej Karpathy
ML papers in the computer science category on arXiv
ML papers in the stats category on arXiv
Distill ML research online journal
Advice and sources for ML:
Advice and sources from ML research student
Better Python REPL:
IPython
bpython
ptpython
Python IDE:
List of IDEs with description
Comparison of IDEs
Emacs Python IDE
Project Jupyter
PyTorch website
PyTorch documentation
PyTorch tutorials
PyTorch online courses
PyTorch examples
Getting help with PyTorch:
PyTorch Discourse forum
Open-access ML preprints:
Arxiv Sanity Preserver by Andrej Karpathy
ML papers in the computer science category on arXiv
ML papers in the stats category on arXiv
Distill ML research online journal
Advice and sources for ML:
Advice and sources from ML research student
Better Python REPL:
IPython
bpython
ptpython
Python IDE:
List of IDEs with description
Comparison of IDEs
Emacs Python IDE
Project Jupyter