The following section serves as a template for Data@Rensselaer’s Jupyter book generator, which helps streamline the process of creating and publishing course websites that implement Jupyter notebooks.
To create a Jupyter book with all of the supporting pages like this (including a Schedule, Session pages, etc.), you must first make sure you have the software necessary to create Jupyter notebooks (i.e. Anaconda) and then install the jupyter-book package. Follow the documentation found in the site’s repository to learn how to create your own book.
Introduction to Machine Learning Applications
General Info
- When: Monday/Thursday 12:00 PM - 2:50 PM
- Where: DCC 308
Contact Info
Jason Kuruzovich (Instructor)
- Email: kuruzj@rpi.edu
- Office location: Pittsburgh 4108
- Office hours: N/A
- Phone: 518-698-9910
Lianlian Jiang (TA)
- Email: jiangl4@rpi.edu
- Office Location: Pittsburgh 2226
- Office hours: N/A
- Phone: N/A
Ask technical questions related to to class to an appropriate slack channel (#homework/#lab). This will ensure that everyone can jump in and help.
I’d prefer that you address other messages to me also through Slack (rather than email). This will enable me to turn off my email while continuing to give priority support to this class.
Course Description
The Schedule for the course.
The Course Materials, including all data and Jupyter notebooks.
The LMS will be used for submissions of projects.
Github will be used for programming assignment collection. See assignments for more detailed procedures.
Slack will be the primary method of communication. Please download the Slack App for your mobile and desktop.
This Dropbox Share will include all presentations.
Prerequisites
None
Textbook
None