- Pickle files that contain serialized scikit-learn (sklearn) models are not guaranteed to be compatible on different architectures, according to this. As the RPi used here has a 32-bit architecture, it is important that the sklearn models are trained and dumped to pickle files using a 32-bit python even if a 64-bit windows machine is used. To do that you can create a new conda environment for that using
conda create -n ml_course_32then activate itconda activate ml_course_32then set the environment to accept 32 bit packages only usingconda config --env --set subdir win-32and then install python usingconda install python=3.7and then install the required packages for each lab as needed includingconda install scikit-learn
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