Demonstration of Backpropagation Algorithm using Neural Networks

[ayan-joshi]

Deep Learning Simplified Repository (Proposing new issue)

:red_circle: Project Title : Backpropagation in Neural Networks :red_circle: Aim : Backpropagation is a fundamental algorithm used for training artificial neural networks. :red_circle: Dataset :

:red_circle: **Approach** : Try to use 3-4 algorithms to implement the models and compare all the algorithms to find out the best fitted algorithm for the model by checking the accuracy scores. Also do not forget to do a exploratory data analysis before creating any model.

---

📍 Follow the Guidelines to Contribute in the Project :

• You need to create a separate folder named as the Project Title.
• Inside that folder, there will be four main components.
  • Images - To store the required images.
  • Dataset - To store the dataset or, information/source about the dataset.
  • Model - To store the machine learning model you've created using the dataset.
  • requirements.txt - This file will contain the required packages/libraries to run the project in other machines.
• Inside the Model folder, the README.md file must be filled up properly, with proper visualizations and conclusions.

---

:red_circle::yellow_circle: Points to Note :

• The issues will be assigned on a first come first serve basis, 1 Issue == 1 PR.
• "Issue Title" and "PR Title should be the same. Include issue number along with it.
• Follow Contributing Guidelines & Code of Conduct before start Contributing.

---

:white_check_mark: To be Mentioned while taking the issue :

• Full name : Ayan Joshi
• GitHub Profile Link : https://github.com/ayan-joshi
• Email ID : [email protected]
• Participant ID (if applicable):
• Approach for this Project : So , I'll first try applying different algorithms then after comparing I'll add the implementation with the best algorithm with its results
• What is your participant role? Yes I'm a part of GSSOC , but Its not only for the program I'm eager to contribute

@abhisheks008 Assign the issue to me

---

Happy Contributing 🚀

All the best. Enjoy your open source journey ahead. 😎