Introduction to Machine Learning¶
We are happy to announce that PACE is offering a series of hands-on workshops on Machine Learning. 2019 November, we offered the first session - Introduction to Machine Learning. This 3-hour hands-on workshop will cover the basic concept of machine learning - supervised learning and unsupervised learning, including neural networks and deep learning. It will also cover the basics of using Scikit-Learn and Tensorflow2 to train your models. We will lead you through code writing and give you short exercises during the session.
You can register here.
We will provide PACE clusters as the computational resource. You will get a follow up email once your registration is confirmed, so that you can setup your account with PACE, and read prerequisite materials. Due to space limits, we cannot guarantee that your spot until you receive a confirmation email. For a long waiting list, we may consider adding another offering soon and we will let you know. Thanks for your understanding.
If you have any questions or suggestions, please contact the course instructor Dr. Nuyun Zhang (Nellie) at firstname.lastname@example.org.
- VPN connection to GT network
- Personal laptop to use during class
- PACE account (New users will be provided a temporary account)
If you are not a PACE user, you will be granted a temporary PACE account after registering for the class. For two weeks, you will have access to PACE resources. Be sure to copy any materials you use during the class off of PACE before your account is deactivated. See instructions for copying files off of PACE via Globus.
Running Python on your local machine¶
You may wish to run Python on your personal computer. To do so, we recommend that you install Anaconda on your laptop.
You can run the workshop materials and Python on your personal computer using Anaconda. Please visit Anaconda and download the software for Mac, Linux, or Windows. Choose the Python 3.7 version. After downloading, please follow the installation instructions. Once installation is complete, open the Anaconda Navigator and choose Jupyter notebook. A browser window should open and load a Jupyter home page.
If you already have Anaconda for Python 2, visit this site for instructions on adding Python 3 support.
Please contact PACE support (email@example.com) if you have any questions or concerns.
Upcoming Course Offerings¶
- Tuesday May 19, 2020, 9:00 AM - 12:00 PM, Blue Jeans
- Wednesday June 10, 2020, 1:30 PM - 4:30 PM, Blue Jeans
- Friday July 10, 2020, 1:30 PM - 4:30 PM, Blue Jeans
Past Course Offerings¶
- Tuesday, November 12, 8:30-11:30AM in Coda Room 114.
- Wednesday, November 13, 8:30-11:30AM in Coda Room 114.