Tutorials

Machine Learning & Deep Learning Tutorials ¶

• This repository contains a topic-wise curated list of Machine Learning and Deep Learning tutorials, articles and other resources. Other awesome lists can be found in this list.

• If you want to contribute to this list, please read Contributing Guidelines.

Linear Regression¶

- [Assumptions of Linear Regression](http://pareonline.net/getvn.asp?n=2&v=8), [Stack Exchange](http://stats.stackexchange.com/questions/16381/what-is-a-complete-list-of-the-usual-assumptions-for-linear-regression)

- [Linear Regression Comprehensive Resource](http://people.duke.edu/~rnau/regintro.htm)

- [Applying and Interpreting Linear Regression](http://www.dataschool.io/applying-and-interpreting-linear-regression/)

- [What does having constant variance in a linear regression model mean?](http://stats.stackexchange.com/questions/52089/what-does-having-constant-variance-in-a-linear-regression-model-mean/52107?stw=2#52107)

- [Difference between linear regression on y with x and x with y](http://stats.stackexchange.com/questions/22718/what-is-the-difference-between-linear-regression-on-y-with-x-and-x-with-y?lq=1)

- [Is linear regression valid when the dependant variable is not normally distributed?](https://www.researchgate.net/post/Is_linear_regression_valid_when_the_outcome_dependant_variable_not_normally_distributed)


Other Tutorials¶

• For a collection of Data Science Tutorials using R, please refer to this list.

• For a collection of Data Science Tutorials using Python, please refer to this list.