Demonstration of Backpropagation Algorithm using Neural Networks

[ayan-joshi]

Deep Learning Simplified Repository (Proposing new issue)

🔴 Project Title : Backpropagation in Neural Networks

🔴 Aim : Backpropagation is a fundamental algorithm used for training artificial neural networks.

🔴 Dataset :

🔴 **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.

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📍 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.

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🔴🟡 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.

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✅ 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

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Happy Contributing 🚀

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

[github-actions]

Thank you for creating this issue! We'll look into it as soon as possible. Your contributions are highly appreciated! 😊

[ayan-joshi]

@abhisheks008 Please have a look I want to contribute

[abhisheks008]

@abhisheks008 Please have a look I want to contribute

I don't think there is any scope of implementing deep learning models for this dataset.

[ayan-joshi]

@abhisheks008 Please have a look I want to contribute

I don't think there is any scope of implementing deep learning models for this dataset.

@abhisheks008 I had one more topic with me
Backpropagation in Neural Networks

should I change this issue to this hope this will match with deep learning ideas ?

[ayan-joshi]

@abhisheks008 Please have a look I want to contribute

I don't think there is any scope of implementing deep learning models for this dataset.

@abhisheks008 I had one more topic with me Backpropagation in Neural Networks

should I change this issue to this hope this will match with deep learning ideas ?

@abhisheks008 Its related to my college project so it will be helpful from you if I get to contribute on this repo , We have a project to contribute to a open source project in ML and last year I contributed to this repo in GSSOC so without hesitating I chose DL simplified to contribute , I'll write a paper about contribution as well

[ayan-joshi]

@abhisheks008 or If u have any thing to add from ur side any issue that will be good as well

[abhisheks008]

Couldn't find any such problem statement behind this project idea.

[ayan-joshi]

Couldn't find any such problem statement behind this project idea.

@abhisheks008 yes but this project will be a great addition to the repo or do u have any idea that should I add to the project that will be very helpful

[abhisheks008]

Can you elaborate the problem statement you are planning to solve here? Are you trying to showcase the implementation of backpropagation in neural networks? Which neural network models/architectures you are going to use here?

Can you clarify on these, it'll be better to understand for me.

[ayan-joshi]

Can you elaborate the problem statement you are planning to solve here? Are you trying to showcase the implementation of backpropagation in neural networks? Which neural network models/architectures you are going to use here?

Can you clarify on these, it'll be better to understand for me.

Backpropagation algorithm is being used for training artificial neural network. It computes the gradient of the loss function with respect to each weight by the chain rule so this ultimately improves the performance of the neural network.

I'll use basic idea of neural network , first forward propagation then the mathematical function and at the end with backward propagation to complete the algorithm.

[abhisheks008]

Can you elaborate the problem statement you are planning to solve here? Are you trying to showcase the implementation of backpropagation in neural networks? Which neural network models/architectures you are going to use here?
Can you clarify on these, it'll be better to understand for me.

Backpropagation algorithm is being used for training artificial neural network. It computes the gradient of the loss function with respect to each weight by the chain rule so this ultimately improves the performance of the neural network.

I'll use basic idea of neural network , first forward propagation then the mathematical function and at the end with backward propagation to complete the algorithm.

Any dataset you are using for this project?