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. Devfolio URL, https://devfolio.co/projects/deep-learning-simplified-f013
Issue Title : Persian Alphabets Classification using NLP #415
Info about the related issue (Aim of the project) : Persian Alphabets Classification using NLP
Name: Kamalakar Satapathi
GitHub ID: Sgvkamalakar
Email ID: sgvkamalakar@gmail.com
Identify yourself: SWOC S4
Closes: #415
Describe the add-ons or changes you've made š
The project adds a novel approach to recognizing Persian characters by combining CNN and LSTM architectures for improved accuracy and robustness.
The models utilize spatial features incase of CNN and temporal patterns incase of LSTM, enhancing accuracy in Persian character recognition.
Data Collection: Image Dataset of Persian characters from Kaggle.
Data Preprocessing: Resize images, split them into train/test sets, and convert them to numerical arrays.
Model Architecture Design: Design CNN, LSTM and hybrid architectures for character recognition.
Model Training: Feed preprocessed data into the model, and train over multiple epochs.
Evaluation: Assess model performance using metrics like accuracy and loss.
Type of change āļø
What sort of change have you made:
[x] New feature (non-breaking change which adds functionality)
How Has This Been Tested? āļø
Describe how it has been tested: Cross-validated the model results using standard evaluation metrics like accuracy and loss.
Describe how have you verified the changes made: Conducted a thorough code review to ensure that the changes align with the project goals and coding standards. You can run the notebook hosted on Kaggle
Checklist: āļø
[x] My code follows the guidelines of this project.
[x] I have performed a self-review of my own code.
[x] I have commented my code, particularly wherever it was hard to understand.
[x] I have made corresponding changes to the documentation.
[x] My changes generate no new warnings.
[x] I have added things that prove my fix is effective or that my feature works.
[x] Any dependent changes have been merged and published in downstream modules.
Pull Request for DL-Simplified š”
Issue Title : Persian Alphabets Classification using NLP #415
Closes: #415
Describe the add-ons or changes you've made š
The project adds a novel approach to recognizing Persian characters by combining CNN and LSTM architectures for improved accuracy and robustness.
The models utilize spatial features incase of CNN and temporal patterns incase of LSTM, enhancing accuracy in Persian character recognition.
Type of change āļø
What sort of change have you made:
How Has This Been Tested? āļø
Describe how it has been tested: Cross-validated the model results using standard evaluation metrics like accuracy and loss.
Describe how have you verified the changes made: Conducted a thorough code review to ensure that the changes align with the project goals and coding standards. You can run the notebook hosted on Kaggle
Checklist: āļø