Custom training loops offer great flexibility. You can quickly add new functionality and gain deep insight into how your algorithm works under the hood. However, setting up custom algorithms over and over is tedious. The general layout often is the same; it’s only tiny parts that change.
A collection of posts on Machine Learning
Training neural networks is a complex procedure. Many variables work with each other, and often it’s unclear what works.
The internet is full of courses and offers many learning materials. You can use these resources to replicate the curriculum of an ML Master’s degree.
Human language is ambiguous. Speaking (or writing), we convey the individual words, tone, humour, metaphors, and many more linguistic characteristics. For computers, such properties are hard to detect in the first place and even more challenging to understand in the second place.
Many universities make their curriculums publicly available, listing all required courses to attain a degree. The Computer Science field is no different. Using such freely accessible resources, one can create a custom schedule.