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krmayankb / repository
The purpose of this repository is to provide beginners with a solid understanding of the fundamental concepts and building blocks of neural networks, machine learning and deep learning.
Welcome to the NeuralNetwork-Foundations repository!
This repository serves as a comprehensive guide and implementation resource for individuals looking to learn and understand the foundations of neural networks, machine learning, and deep learning.
The purpose of this repository is to provide beginners with a solid understanding of the fundamental concepts and building blocks of neural networks. It covers a range of topics including fundamental algorithms like linear regression, logistic regression, etc. to CNN and transformers. It will also add evaluation metrics as the next stage of the project.
Code + Mathematics behind algorithms + examples and more.
To get started with the NeuralNetwork-Foundations, follow these steps:
git clone https://github.com/krmayankb/NeuralNetwork-Foundations.gitcd NeuralNetwork-Foundationscd algorithmsContributions to NeuralNetwork-Foundations are welcome! if you find an issue, have suggestions, or would like to contribute new implementations or tutorials, please feel free to submit a pull request. If you feel there are better ways to organize this repository, please reach out to maintainers. We are open to suggestions and aim to make this repository a go-to repository for learning deep learning.
This repository started with the goal of making learning machine learning fun and easy for individuals. We would like to acknowledge and express our gratitude to the open-source community for their valuable contribution and resources that have helped shape this repository. We will try our best to cite resources that were referred to while writing the codes and while explaining the concepts.
This repository is licensed under the MIT License. Please check the license file for details.