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https://github.com/asherjingkongchen/deep-learn-assign-1

Deep Learning Assignment about: Least Squares, Regression, Logistic, Gradient Descent, Bias-Variance Decomposition, PCA.
https://github.com/asherjingkongchen/deep-learn-assign-1

bias-variance deep-learning gradient-descent least-squares logisitic-regression matplotlib practice primary-component-analysis python pytorch regression-models

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Deep Learning Assignment about: Least Squares, Regression, Logistic, Gradient Descent, Bias-Variance Decomposition, PCA.

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# Deep Learning Assignment 1

In this assignment, I created interactive Jupyter notebooks using [PyTorch](https://pytorch.org/) to build mathematical models.

The notebooks offer hands-on experience with [regression models](https://en.wikipedia.org/wiki/Regression_analysis), allowing students to explore key concepts like model training, optimization, and visualization using [Matplotlib](https://matplotlib.org/) to better understand deep learning in action.

## Get Started

You can open the main notebook file [`main.ipynb`](main.ipynb) or [`main.pdf`](main.pdf) using your favorite viewer.

Please check out the previous results or run the notebook to reproduce the results.

## License

[MIT](LICENSE) © Asher Jingkong Chen

> [!WARNING]
> The data files named in `*.mat` are provided by the course instructor and are not licensed or owned by Asher Jingkong Chen.