ABK: Machine learning & Deep Learning

Exercises and solutions for the course: 66-875 ABK 05: Machine learning and deep learning in the Summer Term 2019 at Hamburg University.

The .ipynb files are Jupyter notebooks for Python 3. Instructions on how to set-up an Anaconda enviroment can be found here.

Lecture material is available on the desycloud.

Name		Name	Last commit message	Last commit date
Latest commit History 19 Commits
img		img
Ex10-Solution.ipynb		Ex10-Solution.ipynb
Ex10.ipynb		Ex10.ipynb
Ex11-Solution.ipynb		Ex11-Solution.ipynb
Ex11.ipynb		Ex11.ipynb
Ex1_Solution.ipynb		Ex1_Solution.ipynb
Ex2.ipynb		Ex2.ipynb
Ex2_Solution.ipynb		Ex2_Solution.ipynb
Ex3.ipynb		Ex3.ipynb
Ex3_Solution.ipynb		Ex3_Solution.ipynb
Ex4-Solution.ipynb		Ex4-Solution.ipynb
Ex4.ipynb		Ex4.ipynb
Ex5-Solution.ipynb		Ex5-Solution.ipynb
Ex5.ipynb		Ex5.ipynb
Ex5_data.npz		Ex5_data.npz
Ex6-Solution.ipynb		Ex6-Solution.ipynb
Ex6.ipynb		Ex6.ipynb
Ex7-Solution.ipynb		Ex7-Solution.ipynb
Ex7.ipynb		Ex7.ipynb
Ex8-Solution.ipynb		Ex8-Solution.ipynb
Ex8.ipynb		Ex8.ipynb
Ex9-Solution.ipynb		Ex9-Solution.ipynb
Ex9.ipynb		Ex9.ipynb
Final_Problem.ipynb		Final_Problem.ipynb
README.md		README.md

Provide feedback