Machine Learning in Python for Environmental Science Problems

Participants will interact with real-world data and a range of machine learning (ML) techniques through a series of Google Collaboratory notebooks. Participant understanding of the concepts will be reinforced with hands-on exercises at the end of each lecture that require implementing the material that was introduced while grappling with the challenges of real-world environmental datasets.

Day 1 will cover AI and ML fundamentals and introduce Python libraries commonly employed for data analysis, ML, and deep learning (DL). Day 2 will provide participants with the option of instruction on more advanced topics in ML/DL following a similar lecture/exercise format as employed on Day 1.

More information provided at the AMS AI Short Course website.