https://github.com/tirendazacademy/end-to-end-deep-learning-projects

This repo contains deep learning techniques to solve a problem from start to finish.
https://github.com/tirendazacademy/end-to-end-deep-learning-projects

Last synced: 3 months ago
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This repo contains deep learning techniques to solve a problem from start to finish.

• Host: GitHub
• URL: https://github.com/tirendazacademy/end-to-end-deep-learning-projects
• Owner: TirendazAcademy
• Created: 2023-01-25T14:03:39.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2023-01-27T20:11:53.000Z (over 2 years ago)
• Last Synced: 2025-06-02T06:57:47.468Z (4 months ago)
• Language: Jupyter Notebook
• Size: 10.9 MB
• Stars: 1
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

          
![](https://github.com/TirendazAcademy/End-to-End-Deep-Learning-Projects/blob/main/image_classification_pytorch_comet/Images/images/end-to-end-projects.png?raw=true)

[![](https://img.shields.io/badge/Python-blue?&style=plastic&logo=python&logoColor=white)]()

[![](https://img.shields.io/badge/Pytorch-470D21?&style=plastic&logo=pytorch&logoColor=white)]()

[![](https://img.shields.io/badge/TensorFlow-darkorange?&style=plastic&logo=tensorflow&logoColor=white)]()

[![](https://img.shields.io/badge/Keras-darkred?&style=plastic&logo=keras&logoColor=white)]()

[![](https://img.shields.io/badge/Lightning-darkblue?&style=plastic&logo=lightning&logoColor=white)]()

[![](https://img.shields.io/badge/FastAI-150050?&style=plastic&logo=fastai&logoColor=white)]()

[![](https://img.shields.io/badge/CometML-E14D2A?&style=plastic&logo=comet&logoColor=white)]()

[![](https://img.shields.io/badge/DeepLearning-CB1C8D?&style=plastic&logo=deeplearning&logoColor=white)]()

This GitHub repository contains a collection of end-to-end deep learning projects implemented using PyTorch, TensorFlow, and Keras frameworks. The projects cover a variety of topics and applications, such as image classification, natural language processing, and generative models.

In addition, we use Comet ML in projects for experiment tracking and visualization, making it easy to keep track of your experiment runs, results, and metrics.

The goal of this repository is to provide a comprehensive resource for those interested in learning about and working with deep learning using these popular frameworks and tools. The code is well-documented and easy to understand, making it a great starting point for anyone looking to dive into the world of deep learning.

We welcome contributions and feedback, so feel free to submit pull requests or open issues if you have any questions or suggestions.