Some good ML Resources:

  1.     Most of the Theory that you’ll need for Machine Learning:
    That’s just right here. Besides this, all you’ll be doing is add up more to this and CODE!

    Start HERE!http://neuralnetworksanddeeplearning.com/chap1.html
    http://machinelearningmastery.com/tutorial-first-neural-network-python-keras/
    http://karpathy.github.io/neuralnets/

  2. You can start looking examples:https://www.kaggle.com/perdox/beginner-nn-recognizer-with-tensorflow-in-python
    https://www.kaggle.com/c/digit-recognizer#tutorial
  3. An introduction to machine learning with scikit-learn

     A comprehensive set of theory and examples (coding!!) with scikit-learn

    http://scikit-learn.org/stable/tutorial/index.html

  4. Another exhaustive source for the NN and basic theory with examples:

    ((It’s kinda like a book). A good place to look for, it’s somewhat comprehensive.http://neuralnetworksanddeeplearning.com/

  5. Check Kaggle for competitions, solved submissions (it has some good solved examples), and datasets or for new problems.

    https://www.kaggle.com
  6. Some pre-prepped Datasets:https://stats.stackexchange.com/questions/169450/what-are-some-good-datasets-to-learn-basic-machine-learning-algorithms-and-why