https://github.com/pilotleoyan/inside-deep-learning

Inside deep learning, a repository to explain and apply deep learning concepts.
https://github.com/pilotleoyan/inside-deep-learning

autograd deep-learning machine-learning-algorithms machine-learning-from-scratch mathematics python3 pytorch

Last synced: about 1 month ago
JSON representation

Inside deep learning, a repository to explain and apply deep learning concepts.

• Host: GitHub
• URL: https://github.com/pilotleoyan/inside-deep-learning
• Owner: PilotLeoYan
• License: mit
• Created: 2024-12-05T18:33:54.000Z (about 2 months ago)
• Default Branch: main
• Last Pushed: 2024-12-14T19:53:47.000Z (about 2 months ago)
• Last Synced: 2024-12-21T18:14:51.837Z (about 1 month ago)
• Topics: autograd, deep-learning, machine-learning-algorithms, machine-learning-from-scratch, mathematics, python3, pytorch
• Language: Jupyter Notebook
• Homepage:
• Size: 733 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Inside Deep learning 🎓

## About



  



This repository aims to bridge the gap between theoretical knowledge and practical implementation in deep learning. Using PyTorch and other modules such as Autograd, we explore the complexity of different models and algorithms and make them accessible to both students and practitioners.

## Table of Contents

1. [Linear regression](1-linear-regression)

   1. [Simple linear regression](1-linear-regression/1-1-simple-linear-regression.ipynb)

   2. [Multivariate linear regression](1-linear-regression/1-2-multivariate-linear-regression.ipynb)

2. [Classification](2-classification)

   1. [Multiclass classification](2-classification/2-1-multiclass-classification.ipynb)

   2. [softmax function and its derivative](2-classification/softmax-function-and-its-derivative.ipynb)

4. [Multilayer Perceptron](3-multilayer-perceptron)

   1. [MLP](3-multilayer-perceptron/3-1-mlp.ipynb)

   2. [gradients and activation functions](3-multilayer-perceptron/gradients-and-activation-functions.ipynb)

   3. [mlp for classification](3-multilayer-perceptron/mlp-for-classification.ipynb)

   4. [mlp like pytorch](3-multilayer-perceptron/mlp-like-pytorch.ipynb)

## How to Use

1. Clone the repository:

   ```bash

   git clone https://github.com/PilotLeoYan/inside-deep-learning.git

   ```

2.

   A. Install dependencies with cuda:

   ```bash

   pip install -r requirements-cuda.txt

   ```

   B. Install dependencies without cuda:

   ```bash

   pip install -r requirements.txt

   ```

## Used hardware

* CPU: AMD A6-9500

* GPU: Nvidia Geforce RTX 2070-SUPER (8GB VRAM)

* RAM: 16GB DDR4

## Contributing

Contributions are welcome! If you have suggestions, improvements, or new topics to add, feel free to open an issue. Please follow the [contributing guidelines](CONTRIBUTING.md).

Remember that I am only one person working on this repository 🐱‍👤.

---

If you would like to contact me you can send me an [email](mailto:[email protected]).

**Happy Learning!** 🎓