Machine Learning for Engineers

Course (C) and Labs (L).  -- Graded labs are in bold.
In general, labs are made available the same day as the course.
Information is up-to-date until 12.10. Missing information will be provided soon (this comment will be removed once it is finalized)

Date	Morning	Afternoon
Thu. 21.09.2023	(C) 1. ML introduction	(L) Lab "intro-to-python" + Lab "optimization"
Thu. 28.09.2023	(C) 2. Bayesian 1	(C) 3. Bayesian 2
Thu. 05.10.2023	(L) Lab "Bayesian 1" + "Bayesian 2" (due 11.10)	(L) Feedback on "python" and "optimization" and "Bayesian 1" + continuation of Lab on "Bayesian 2"
Thu. 12.10.2023	(C) 4. Hidden Markov Models	(L) Lab "hmm" (due 18.10.2023)
Thu. 19.10.2023	(C) 5. Dimensionality reduction	(L) Feedback : "Bayesian 2"
Thu. 26.10.2023	(C) 6. Decision trees	(L) Lab "decision-trees" (due 08/11)
Thu. 02.11.2023	(C) 7. Linear regression	(L) Lab "linear-regression" (due 08.11.2023)
Thu. 09.11.2023	(C) 8. Nonlinear regression	(L) Lab "non-linear-regression" (due 15.11.2023)
Thu. 16.11.2023	(C) 9. Kernel Methods - SVM	(L) Lab "kernel-methods"
Thu. 23.11.2023	(C) 10. Tensor factorization	(L) Feedback "decision-tree" - Lab "tensor-factorization" (due 29.11.2023)
Thu. 30.11.2023	(C) 11. Deep learning 1	(L) Feedback "kernel-methods" - Lab "intro-to-pytorch"
Thu. 07.12.2023	(C) 12. Deep learning 2	(L) Feedback "intro-to-pytorch" - Lab "convnets"
Thu. 14.12.2023	(C) 13. Deep learning 3	(L) Feedback "convnet" - Lab "finetuning" (due 19.12)
Thu. 21.12.2023	(C) 14. Deep learning 4