M. Pawan Kumar
 
 

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NOTES

Project Notes: Optimization Methods for Linear Regression
PDF

Lecture: Linear Regression
PPT   PDF

COURSE MATERIAL

Take care when unpacking archives not to overwrite existing material with the same file names. The following zip file should be handled properly by any OS and will unzip into directory B1 and subdirectories. The gzipped tar file works on Linux (use the command "tar zvxf B1.tgz").

Source Code and Project Notes
ZIP   TGZ

REAL WORLD DATA

Once you have implemented a regression algorithm and tested it on the synthetic data set, please use the Boston Housing data set to generate results. The dataset consists of 506 samples, with 14 features. Use the first 13 features as the input, and the final feature (MEDV) as the target output. Use the first 306 samples for training and the last 200 samples for testing.

ERRATA

Any errors found in the notes/code will be discussed here.