A from scratch implementation of Linear Regression algorithm with 2 fitting parameters. The parameters are optimised using Gradient Descent algorithm. The implementation also utilises GNUplot to plot the data and cost over epochs.
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Clone the repo into your folder
git clone https://github.com/sanjeev309/linear_regression_using_GD
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Experiment with values of EPOCH, LEARNING_RATE and default theta values in main.cpp
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Execute make command to compile into an executable
make compile
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Run the executable
./linear_reg
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Clean for a rebuild
make clean
*nix OS, gcc compiler, basic C programming and curiosity.
- Sanjeev Tripathi - LinkedIn
This project is licensed under the MIT License - see the LICENSE file for details
- This project dates back to 3+ years when I just began with Andrew Ng's ML course in MATLAB. A lot of gratitude for him and the initiative.