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  • Theory of data science for Machine learning?

    I am looking for a good book, article or course that talks about the theory and tools behind data analysis for Machine-learning. I am NOT looking for how to run the tools like Nural Networks or SVM. A few questions that I am trying to answer are:
    How to gain insight into the data if the classifiers give strange results?
    What all factors affect the results?
    How can I break down the data before and after building classifiers to explain what results I am getting?
    How does pre-processing the data affect the results?
    What things to keep in mind before building classifiers?
    How can I tell I am under-training or over-training? How can I avoid both?
    Almost like data science but with focus on Machine learning.
    Any recommendations?
    Thanks so much in advance

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