Inside Deep Learning - Inside Deep Learning

Python Version PyTorch Version Jupyter Notebook Latest commit Number of issues Number of PRs License

Inside Deep Learning is a collection of Jupyer notebooks aimed at exploring the vast field of machine learning. Sometimes it is difficult to find implementations of important concepts or ideas, so here we try to implement and explain those ideas using Jupyter Notebooks and PyTorch.

This repository is not intended for beginners or LMs lovers. Rather, it is a compilation of notes on all possible ML topics, especially DL.

Recommended references 📚️: Deisenroth et al. (2020), Goodfellow et al. (2016), Zhang et al. (2023).

Table of Contents¶

How to Clone¶

Clone the repository:

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

Create environment:
Inside Deep Learning is written in python=3.14.0. We recommend using Conda to manage dependencies.
```
conda create --name idl -y python=3.14.0
conda activate idl
pip install --upgrade pip
cd inside-deep-learning
```
A. Install dependencies with cuda:
```
pip install -r requirements-cuda.txt
```
B. Install dependencies without cuda:
```
pip install -r requirements.txt
```

Contributing¶

If you find this repo useful, please star (★) this repo or cite using the following bibtex entry:

@misc{pilotleoyan25idl,
  title={Inside-Deep-learning},
  author={Rivera, Leonardo Fabyan Ortega},
  publisher = {GitHub},
  journal = {GitHub repository},
  howpublished={\url{https://github.com/PilotLeoYan/inside-deep-learning}},
  year={2025}
}

>>> Github Repository: Inside Deep Learning <<<

Star History¶

If you would like to contact me you can send me an email.

References¶

Deisenroth, M. P., Faisal, A. A., & Ong, C. S. (2020). Mathematics for machine learning. Cambridge University Press.
Goodfellow, I., Bengio, Y., & Courville, A. (2016). Deep Learning. MIT Press.
Zhang, A., Lipton, Z. C., Li, M., & Smola, A. J. (2023). Dive into Deep Learning. Cambridge University Press.