EPISODE · Feb 11, 2017 · 8 MIN
How to Make Data Amazing - Intro to Deep Learning #5
from Siraj Raval
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 Please subscribe. And like. And comment. That's what keeps me going. 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 Join us in our Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
What this episode covers
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 Please subscribe. And like. And comment. That's what keeps me going. 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 Join us in our Slack channel: http://wizards.herokuapp.com/ And please support me on Patreon: https://www.patreon.com/user?u=3191693 Follow me: Twitter: https://twitter.com/sirajraval Facebook: https://www.facebook.com/sirajology Instagram: https://www.instagram.com/sirajraval/ Instagram: https://www.instagram.com/sirajraval/
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How to Make Data Amazing - Intro to Deep Learning #5
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