We are very excited to announce a training event on Machine Learning/Deep Learning organised through the HEP Software Foundation and IRIS-HEP
All sessions will take place in the US Eastern Time zone.
Please contact the organizers (email us) in case of any questions.
What exactly will I learn?
The main objective of this course are
-
To introduce you to the basics of Machine learning with examples.
-
To develop a sense of statistics/data science algorithms that goes under the hood of a ML model.
-
Explain the terminology of machine learning.
-
Introducing you to some Python frameworks to start building your first Machine.
-
Getting familiarize with basic ML models that are although very common but can serve as a basic starting point.
-
Getting you prepared to learn on your own once this course is over.
Are there any prerequisites?
Yes!
Hard Prerequisites
Participants should have basic experience with Python, including writing or modifying simple scripts, using functions and packages, and understanding simple error messages. You should also be able to run and edit a Jupyter Notebook or Google Colab notebook, use basic terminal commands, and install Python packages when needed. A working Python environment is required; Google Colab will be supported, although a local conda, mamba, or pip environment is encouraged for the exercises.
Soft Prerequisites
Basic familiarity with functions, vectors and matrices, derivatives, probability, and statistics will be helpful. Prior experience with NumPy, Pandas, plotting, Scikit-Learn, PyTorch, Git, machine learning, or HEP data analysis is useful but not required. The course is intended for participants with different levels of ML experience, but it will not provide an introduction to Python programming.
Who is supporting this?
This event is supported by CERN and U.S. National Science Foundation Cooperative Agreement PHY-2323298 (IRIS-HEP).
Who is teaching this thing?
This is a hands-on training and consists of live lectures by the instructors via Zoom. Along with this, there are mentors who will give individual attention and to debug assistance to participants via chat tools. The people filling these roles are listed below.
Instructors:
-
- Arghya Chattopadhyay (University of Puerto Rico Mayaguez)
Mentors (on Slack):
- Quinn Campagna (University of Mississippi)
- Mateo E Lisondo (University of Puerto Rico Mayaguez)
- Karan Singh
- Aashirvad (Manipal Academy of Higher Education)
- Juvenal Bassa (University of Puerto Rico Mayaguez)