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## 🔴 Welcome contributors!
Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data. Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. The concept of deep learning is not new. It has been around for a couple of years now. It’s on hype nowadays because earlier we did not have that much processing power and a lot of data. As in the last 20 years, the processing power increases exponentially, deep learning and machine learning came in the picture. </br> </br>
**Deep Learning Simplified is an Open-source repository, containing beginner to advance level deep learning projects for the contributors, who are willing to start their journey in Deep Learning.**
Deep learning is a subset of machine learning, which is essentially a neural network with three or more layers. These neural networks attempt to simulate the behavior of the human brain—albeit far from matching its ability—allowing it to “learn” from large amounts of data. Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction. The concept of deep learning is not new. It has been around for a couple of years now. It’s on hype nowadays because earlier we did not have that much processing power and a lot of data. In the last 20 years, the processing power has increased exponentially, and deep learning and machine learning have come into the picture. </br> </br>
**Deep Learning Simplified is an Open-source repository, containing beginner to advanced-level deep learning projects for contributors, who are willing to start their journey in Deep Learning.**

## Structure of the Projects 📝
This repository consists of various machine learning projects, and all of the projects must follow a certain template. I wish the contributors will take care of this while contributing in this repository. <br><br>
**Dataset** - This folder stores the dataset used in this project. If the Dataset is not being able to uploaded in this folder due to the large size, then put a README.md file inside the Dataset folder and put the link of the collected dataset in it. That'll work!<br><br>
**Images** - This folder is used to store the images generated during the data analysis, data visualization, data segmentation of the project.<br><br>
**Model** - This folder would have your project file (that is .ipynb file) be it analysis or prediction. Other than project file, it should also have a **'README.md'** using this [template](https://github.com/abhisheks008/DL-Simplified/blob/main/.github/readme_template.md) and **'requirements.txt'** file which would be enclosed with all needed add-ons and libraries that are included in the project.</br></br>
This repository consists of various machine learning projects, and all of the projects must follow a certain template. I hope the contributors will take care of this while contributing to this repository. <br><br>
**Dataset** - This folder stores the dataset used in this project. If the Dataset is not able to upload in this folder due to the large size, then put a README.md file inside the Dataset folder and put the link of the collected dataset in it. That'll work!<br><br>
**Images** - This folder is used to store the images generated during the data analysis, data visualization, and data segmentation of the project.<br><br>
**Model** - This folder would have your project file (that is .ipynb file) be it analysis or prediction. Other than the project file, it should also have a **'README.md'** using this [template](https://github.com/abhisheks008/DL-Simplified/blob/main/.github/readme_template.md) and **'requirements.txt'** file which would be enclosed with all needed add-ons and libraries that are included in the project.</br></br>
Please follow the [Code of Conduct](https://github.com/abhisheks008/DL-Simplified/blob/main/Code_of_conduct.md) and [Contributing Guidelines](https://github.com/abhisheks008/DL-Simplified/blob/main/CONTRIBUTING.md) while contributing in this project repository.

## 🧮 Workflow
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- Comment out in the issue, you wanna work on.
- Wait for the issue to be assigned to you. Once it's assigned to you, start working on it.
- Fork the repository.
- Clone your forked repository using terminal or gitbash. Also you can simply use the web version of GitHub to add your files.
- Clone your forked repository using terminal or gitbash. Also, you can simply use the web version of GitHub to add your files.
- Make changes to the cloned repository.
- Add, Commit and Push.
- Add, Commit, and Push.
- Then in Github, in your cloned repository find the option to make a pull request.
- Project admin will evaluate your PR and provide remarks accordingly. If it satisfies all the criterias, your PR will be merged and your contributions will be counted.
The project admin will evaluate your PR and provide remarks accordingly. If it satisfies all the criteria, your PR will be merged and your contributions will be counted.


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</table>

## 🤔 New to Open Source programs/events!
Here are few articles which will help you to get an idea on how you start contributing in open source projects,
Here are a few articles that will help you get an idea of how you start contributing to open-source projects,
You can refer to the following articles on the basics of Git and Github.
- [Watch this video to get started, if you have no clue about open source](https://youtu.be/SYtPC9tHYyQ)
- [Forking a Repo](https://help.github.com/en/github/getting-started-with-github/fork-a-repo)
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****************************************************************
<h2>✨Top Contributors</h2>

Thanks goes to these Wonderful People. Contributions of any kind are welcome!🚀
Thanks go to these Wonderful People. Contributions of any kind are welcome!🚀

<!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section -->
<!-- prettier-ignore-start -->
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