https://github.com/amr-yasser226/deep-learning-journal
A personal collection of Jupyter notebooks, scripts, and resources documenting my exploration and learning in Deep Learning. From foundational neural network concepts to advanced transformer architectures, this repo tracks experiments, notes, and implementations.
https://github.com/amr-yasser226/deep-learning-journal
ai computer-vision deep-learning jupyter keras machine-learning neural-networks nlp notebook pytorch tensorflow
Last synced: 3 months ago
JSON representation
A personal collection of Jupyter notebooks, scripts, and resources documenting my exploration and learning in Deep Learning. From foundational neural network concepts to advanced transformer architectures, this repo tracks experiments, notes, and implementations.
- Host: GitHub
- URL: https://github.com/amr-yasser226/deep-learning-journal
- Owner: amr-yasser226
- Created: 2025-06-15T12:55:31.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-07-14T15:45:14.000Z (12 months ago)
- Last Synced: 2025-07-14T20:02:10.713Z (12 months ago)
- Topics: ai, computer-vision, deep-learning, jupyter, keras, machine-learning, neural-networks, nlp, notebook, pytorch, tensorflow
- Language: Jupyter Notebook
- Homepage:
- Size: 13.9 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Deep Learning Journal
This repository serves as a professional, chronological record of my deep learning education. It captures all notebooks, code samples, experiments, and detailed notes that reflect both completed studies and ongoing exploration.
Every entry documents the concepts and techniques I have mastered, as well as areas currently under investigation. By maintaining these materials in a single location, I ensure reproducibility, clear organization of my progress, and a transparent view of my evolving understanding of neural network theory and practice.
All resources are presented in Jupyter notebook format with accompanying narrative explanations to illustrate objectives, methodologies, and outcomes. This collection is intended for self‑review, collaboration, and reference as I advance through foundational principles to cutting‑edge architectures.
Added: I discovered that almost everyone is working with TF-Keras, so, I guess I have to do the Music Generation again but this time with TF, even though I know pytorch
Added: So I discovered that our university doesn't pay that much attention to the
deep learning labs, and that's bad yea,
Added: Still don't understand the real difference between PyTorch, TensorFlow, and Keras, and I also don't understand almost all job offers requires both of them!, like why would you make a model with TensorFlow, then make another model in the same company with PyTorch!! I don't get it
Added: I think I'll start a big end-to-end ML project soon