Analytics and AI: Machine Learning

RECOMMENDED:

• Familiarity with probability/statistics and algorithms

REQUIRED:

• Proficiency in Python or MATLAB programming
• Strong numerate background

REQUIRED (Student must provide):

• Internet connection
• Free software (download and install before taking the course)
  • Python programming language (see www.python.org) or MATLAB (see https://www.mathworks.com/products/matlab/student.html)
  • Adobe Acrobat PDF reader (see get.adobe.com/reader/)
  • Any zip tool (e.g., https://www.7-zip.org/)
  • Recommended, but not required: any LaTeX editor (e.g., www.overleaf.com)
• Laptop or desktop computer (not a tablet)
• Reference books (Not required)
  • (PRML) C.M. Bishop. Pattern Recognition and Machine Learning
  • (ESL) T. hastie, R. Tibshirani, J. Friedman. The Elements of Statistical Learning: Data Mining, Inference, and Predictions, 2nd ed.
  • (FML) M. Mohri, A. Rostamizadeh, A. Talwalkar. Foundations of Machine Learning, 2nd ed.

PROVIDED (Student will receive):

• All course lessons, slides, assignments, solutions

• Claim your Georgia Tech (GT) account, set up your GT account password and view your GT account user name. This account is different from your account and password on this website.
  • Claim your Georgia Tech (GT) account OR
  • Check your inbox for an email with a direct link.
    NOTE: It may take up to an hour from registration for your GT account to be established and the email to be sent. We appreciate your patience.
• Note your GT username and password. You will need both to access your course materials.
• Log in to your course with the course platform delivery link below.

Canvas: https://gatech.instructure.com/