Julia Programming for Machine Learning course (JuML) offered by Prof. Klaus-Robert Müller’s Machine Learning Group at TU Berlin.
Syllabus:
| Week | Lecture | Content |
|---|---|---|
| 1 | 0 | General Information, Installation & Getting Help |
| 1 | Basics 1: Types, Control-flow & Multiple Dispatch | |
| 2 | 2 | Basics 2: Arrays, Linear Algebra |
| 3 | Plotting & DataFrames | |
| 3 | 4 | Basics 3: Data structures and custom types |
| 5 | Classical Machine Learning | |
| 4 | 6 | Automatic Differentiation |
| 7 | Deep Learning | |
| 5+ | Project | Workflows: Scripts, Experiments & Packages |
| Project | Profiling & Debugging |