Testing Assumptions - Practical Machine Learning Tutorial with Python p.12

Channel:
United States sentdex
Subscribers:
1,410,000
Published on ● Video Link: https://www.youtube.com/watch?v=Kpxwl2u-Wgk


Category:
Tutorial
Duration: 20:33
110,340 views
1,266

We've been learning about regression, and even coded our own very simple linear regression algorithm. Along with that, we've also built a coefficient of determination algorithm to check for the accuracy and reliability of our best-fit line. We've discussed and shown how a best-fit line may not be a great fit, but also explained why our example was correct directionally, even if it was not exact. Now, however, we are at the point where we're using two top-level algorithms, which are subsequently comprised of a handful of smaller algorithms. As we continue building this hierarchy of algorithms, we might wind up finding ourselves in trouble if just one of them have a tiny error, so we want to test our assumptions.

https://pythonprogramming.net/sample-data-testing-machine-learning-tutorial/
https://twitter.com/sentdex
https://www.facebook.com/pythonprogramming.net/
https://plus.google.com/+sentdex



Other Videos By sentdex


2016-05-17Support Vector Assertion - Practical Machine Learning Tutorial with Python p.22
2016-05-16Understanding Vectors - Practical Machine Learning Tutorial with Python p.21
2016-05-13Support Vector Machine Intro and Application - Practical Machine Learning Tutorial with Python p.20
2016-05-11Final thoughts on K Nearest Neighbors - Practical Machine Learning Tutorial with Python p.19
2016-05-09Applying our K Nearest Neighbors Algorithm - Practical Machine Learning Tutorial with Python p.18
2016-05-06Writing our own K Nearest Neighbors in Code - Practical Machine Learning Tutorial with Python p.17
2016-05-05Creating Our K Nearest Neighbors Algorithm - Practical Machine Learning with Python p.16
2016-05-03Euclidean Distance - Practical Machine Learning Tutorial with Python p.15
2016-05-01K Nearest Neighbors Application - Practical Machine Learning Tutorial with Python p.14
2016-04-29Classification w/ K Nearest Neighbors Intro - Practical Machine Learning Tutorial with Python p.13
2016-04-26Testing Assumptions - Practical Machine Learning Tutorial with Python p.12
2016-04-23Programming R Squared - Practical Machine Learning Tutorial with Python p.11
2016-04-21R Squared Theory - Practical Machine Learning Tutorial with Python p.10
2016-04-18How to program the Best Fit Line - Practical Machine Learning Tutorial with Python p.9
2016-04-17How to program the Best Fit Slope - Practical Machine Learning Tutorial with Python p.8
2016-04-16Regression How it Works - Practical Machine Learning Tutorial with Python p.7
2016-04-14Pickling and Scaling - Practical Machine Learning Tutorial with Python p.6
2016-04-13Regression forecasting and predicting - Practical Machine Learning Tutorial with Python p.5
2016-04-12Regression Training and Testing - Practical Machine Learning Tutorial with Python p.4
2016-04-11Regression Features and Labels - Practical Machine Learning Tutorial with Python p.3
2016-04-10Regression Intro - Practical Machine Learning Tutorial with Python p.2


Tags:
machine learning
python
tutorial
artificial intelligence
scikit-learn
theano
tensorflow
nearest neighbors
k nearest neighbors
knn
algorithm