How to Make Data Amazing - Intro to Deep Learning #5

In this video, we'll go through data preprocessing steps for 3 different datasets. We'll also go in depth on a dimensionality reduction technique called Principal Component Analysis.

Coding challenge for this video:
https://github.com/llSourcell/How_to_Make_Data_Amazing

Charles-David's Winning Code:
https://github.com/alkaya/earthquake-cotw

Siby Jack Grove's Runner-up code:
https://github.com/sibyjackgrove/Earthquake_predict/blob/master/earthquake_predict.ipynb

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More Learning Resources:
http://www.cs.ccsu.edu/~markov/ccsu_courses/datamining-3.html
http://www.slideshare.net/jasonrodrigues/data-preprocessing-5609305
http://iasri.res.in/ebook/win_school_aa/notes/Data_Preprocessing.pdf
http://staffwww.itn.liu.se/~aidvi/courses/06/dm/lectures/lec2.pdf
http://ufldl.stanford.edu/wiki/index.php/Data_Preprocessing
http://machinelearningmastery.com/how-to-prepare-data-for-machine-learning/
https://plot.ly/ipython-notebooks/principal-component-analysis/

Public datasets:
https://github.com/caesar0301/awesome-public-datasets
https://aws.amazon.com/public-datasets/
http://archive.ics.uci.edu/ml/index.html
https://dreamtolearn.com/ryan/1001_datasets

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Видео How to Make Data Amazing - Intro to Deep Learning #5 канала Siraj Raval