https://www.dataquest.io/blog/free-datasets-for-projects/
http://www.dataschool.io/comparing-supervised-learning-algorithms/
https://homes.cs.washington.edu/~pedrod/papers/cacm12.pdf
https://www.quora.com/Whats-worse-a-false-positive-or-false-negative-in-machine-learning
https://www.quora.com/What-is-the-difference-between-a-parametric-model-and-a-non-parametric-model
https://en.wikipedia.org/wiki/Oversampling_and_undersampling_in_data_analysis
https://www.quora.com/How-do-we-decide-which-algorithm-to-use-in-machine-learning
https://www.youtube.com/watch?v=aircAruvnKk&list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi
https://pandas.pydata.org/pandas-docs/stable/comparison_with_sql.html
https://math.stackexchange.com/questions/1681699/is-this-histogram-considered-bimodal
https://www.youtube.com/watch?v=FmpDIaiMIeA
https://www.thecodeship.com/general/hackathon-toolbox-essential-tools-practices/
- Pandas Cheat-sheet
https://github.com/pandas-dev/pandas/blob/master/doc/cheatsheet/Pandas_Cheat_Sheet.pdf
- Numpy Cheat-sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Numpy_Python_Cheat_Sheet.pdf
- Scikitlearn Cheat-sheet
https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf