https://github.com/doniaskima/deep-learning-with-tensorflow
https://github.com/doniaskima/deep-learning-with-tensorflow
Last synced: about 1 month ago
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- Host: GitHub
- URL: https://github.com/doniaskima/deep-learning-with-tensorflow
- Owner: doniaskima
- Created: 2023-10-08T20:00:26.000Z (over 1 year ago)
- Default Branch: master
- Last Pushed: 2023-10-26T13:48:27.000Z (over 1 year ago)
- Last Synced: 2025-01-22T05:27:59.830Z (3 months ago)
- Language: Jupyter Notebook
- Size: 2.8 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.MD
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README
# Deep Learning Concepts Learning Repository
Welcome to the Deep Learning Concepts Learning Repository! This repository is dedicated to helping you understand and explore the fundamental concepts and techniques in the field of deep learning.
## Table of Contents
- [Introduction](#introduction)
- [Getting Started](#getting-started)
- [Repository Structure](#repository-structure)
- [Contributing](#contributing)
- [Resources](#resources)
- [License](#license)
## Introduction
Deep learning is a subset of machine learning that deals with neural networks and algorithms inspired by the structure and function of the human brain. It has gained immense popularity due to its ability to solve complex tasks such as image and speech recognition, natural language processing, and more.
This repository is your one-stop resource for diving into deep learning concepts, from the basics to advanced topics. Whether you're a beginner or an experienced practitioner, you'll find a wealth of materials and code samples to help you learn and experiment with deep learning.
## Getting Started
To get started with learning deep learning concepts, follow these steps:
1. **Clone the Repository**: Start by cloning this repository to your local machine:
git clone https://github.com/doniaskima/Deep-learning-with-tensorflow
2. **Explore the Content**: Browse the repository's directories to access educational materials, code examples, and resources on deep learning.
3. **Run Code Samples**: Experiment with the provided code samples and tutorials to gain hands-on experience.
4. **Contribute**: If you have insights, improvements, or additional resources to share, please consider contributing to the repository.
## Contributing
We welcome contributions from the deep learning community! If you have any insights, additional tutorials, code improvements, or resources to share, please consider contributing to this repository. Check the [CONTRIBUTING.md](CONTRIBUTING.md) file for guidelines on how to contribute.
## Resources
Here are some external resources to supplement your deep learning journey:
- [Deep Learning Specialization on Coursera](https://www.coursera.org/specializations/deep-learning) by Andrew Ng.
- [Deep Learning Book](http://www.deeplearningbook.org/) by Goodfellow, Bengio, and Courville.
- [Stanford University's CS231n Course](http://cs231n.stanford.edu/): Convolutional Neural Networks for Visual Recognition.
## License
This repository is open-source and available under the [MIT License](LICENSE). Feel free to use the materials and code for personal and educational purposes.
Happy learning!
Remember to replace your-username in the repository URL with your actual GitHub username when you create your repository. You can customize this README to suit your specific content and goals for the repository.