Danke für diesen lehrreichen Kurs!

Welcome (old)
#1

I´m in my late fifties and working as an IT hardware repair technician for over 30 years. Three years ago I had to learn the Python language to be able to program a Raspberry Pi which I bought out of curiosity. It only took a few weeks to realize that python is heavily used in the fields of artificial intelligence. So I learned about neurons and deep learning and so on mainly using Keras and Tensorflow framework. The only contact I had so far with scikit-learn was the train_test_split() function which I used in almost every model building process.

Luckily this MOOC was proposed to me somewhere online (Twitter?) and I gave it a try and I don´t regret it.
Finally I got a deeper insight into the world of scikit-learn.

I greatly appreciated the Jupyter notebooks as I work almost exclusively in this environment. The MOOC curriculum was very well divided into the seven modules that built on each other and introduced us step by step to the respective subject.

I would like to thank the whole MOOC team for their work and their efforts you all put into this course to make it work. It was my pleasure to participate and learn a lot.

Applause to you all, great work!

Best regards,
Thomas

#2

Thank you very much for sharing your experience with us and for your contributions in helping others on the forum. Continuous learning and professional development was one of our main objectives for this MOOC so I am really glad it worked for you!

train_test_split is everyone’s favorite function and probably the most successful contribution of the scikit-learn project to the data-scientists’ productivity :wink:

Just a note about Jupyter notebooks: they are very nice for interactive exploratory work, teaching and reporting but we also recommend learning how to structure a project in plain python files with packages, submodules, and automated tests.

For this you can use jupyterlab as an IDE but more advanced full-featured IDEs are even nicer, for instance VS Code and its Python extension.

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