:) files and simple description for practice
- python programming,
- EDA for datasets,
- simple ML topics
- MLops tools usage,
- ...
In folder git-github
you can find:
- commiting ipynb (init, add, commit, status, log)
- branching ipynb (branch, switch, checkout)
- merging ipynb (merge, fast forward merge, auto-resolve conflicts, manually resolve conflicts)
In folder probabilistic-ml
you can find:
- keynotes,
- tasks and solutions. Main source is Probabilistic Machine Learning: An Introduction the book written by Kevin P. Murphy.