Notes

• Neural networks: more architectures
• Neural networks (beginning with the perceptron)
• Logistic regression
• Gradient descent
• Classification, continued
• Classification
• Clustering
• Fundamental concepts in AI/ML
• Dimensional Reduction
• Filtering and resampling
• Data characterization
• Accessing data
• Data: Types, formats, and availability
• Introductions
• Putting together your coding ecosystem
• An introduction to ESS 469/569