This is one of the most used machine learning models ever. Random Forests can be used for both regression and classification, and our use case will be to assess whether someone is credible or not by analyzing their financial history!
DL nanodegree open for another round! we'll pick one random student that signs up in next 24 hrs to collab w/ me one-on-one on a DL music project
https://www.udacity.com/course/deep-learning-nanodegree-foundation--nd101
Code for this video:
https://github.com/llSourcell/random_forests
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More learning resources:
https://ujjwalkarn.me/2016/05/30/a-curated-list-of-python-tutorials-for-data-science-nlp-and-machine-learning/
https://www.coursera.org/learn/machine-learning-data-analysis/lecture/eTO92/building-a-random-forest-with-python
https://github.com/kevin-keraudren/randomforest-python
http://kldavenport.com/pure-python-decision-trees/
http://blog.yhat.com/posts/random-forests-in-python.html
https://www.analyticsvidhya.com/blog/2016/04/complete-tutorial-tree-based-modeling-scratch-in-python/
http://machinelearningmastery.com/implement-decision-tree-algorithm-scratch-python/
http://machinelearningmastery.com/implement-random-forest-scratch-python/
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