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collect your experiences here. This should include how to install the tool, what it can do for feature extraction and classification, and your experiences (easy? limited? data import, etc.). Also try to keep this brief.
People learn in different ways. I often like to start with a tutorial , make sure it works , and then gradually migrate from their data / features to my data and features. Some people like to start with the theory. Others start with the manual and build their own implementation.
Explored by PMR:
Hmm. I thought I had Python installed and wasted 10 minutes before I realised I didn't. I tried pip and only later realised that we now need pip3
Moral. READ THE DOCS FROM THE START. I found https://www.digitalocean.com/community/tutorials/how-to-install-python-3-and-set-up-a-local-programming-environment-on-macos (there are similar tutorials for other OS's).
It also explained my_env. Note try to find a recent tutorial. Many systems are still fluid.
Time: ca 20 minutes (includes reading the docs! and checking before issuing commands (typos in installation can be a nightmare)
Easy if I had done it carefully. I now have a virtual Python environment my_env/.
https://www.digitalocean.com/community/tutorials/how-to-build-a-machine-learning-classifier-in-python-with-scikit-learn Explored by PMR:
- Python 3
- Jupyter Notebook
- Time
- problems