Website Classification

[manishh12]

Pull Request for DL-Simplified 💡

Issue Title : Website Classification

• Info about the related issue (Aim of the project) :The aim of the project is to classify URLs into different categories based on their content. This classification task involves training machine learning models to accurately predict the category of a given URL.
• Name: Manish Kumar Gupta
• GitHub ID: manishh12
• Email ID: manishdid360@gmail.com
• Idenitfy yourself: (Mention in which program you are contributing in. Eg. For a JWOC 2022 participant it's, JWOC Participant) GSSOC'24

Closes: #606 #627

Describe the add-ons or changes you've made 📃

The aim is to classify URLs into predefined categories such as adult content, arts, business, computers, games, health, home, kids, news, recreation, reference, science, shopping, society, or sports. The project involves preprocessing the dataset, visualizing the distribution of categories, training the models, and evaluating their performance.

Implemented the CNN model architecture, including embedding, convolutional, max pooling, flatten, dropout, and dense layers. Trained the CNN model using the provided dataset and evaluated its performance.

Plotted the training and validation loss values as well as the training and validation accuracy values for the CNN model.

Defined the BiLSTM model architecture, consisting of embedding, bidirectional LSTM, and dense layers.

Compiled and trained the BiLSTM model on the dataset.

Generated plots showing the accuracy and loss curves for the BiLSTM model.

The modifications include adding detailed descriptions of the CNN and BiLSTM model architectures, training the models, evaluating their performance, and visualizing the training progress through loss and accuracy plots. Additionally, explanations were provided for training the models for fewer epochs due to resource constraints, which may affect the achieved accuracy.

What sort of change have you made:

• [ ] Bug fix (non-breaking change which fixes an issue)
• [x] New feature (non-breaking change which adds functionality)
• [ ] Code style update (formatting, local variables)
• [ ] Breaking change (fix or feature that would cause existing functionality to not work as expected)
• [ ] This change requires a documentation update

How Has This Been Tested? ⚙️

Describe how it has been tested Describe how have you verified the changes made

Checklist: ☑️

• [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.
• [ ] Any dependent changes have been merged and published in downstream modules.

[github-actions[bot]]

Our team will soon review your PR. Thanks @manishh12 :)

[manishh12]

@abhisheks008 Due to resource constraints, including limited GPU allocation, frequent runtime disconnects across multiple accounts, and the substantial size of the dataset, I could only implement two models: CNN and BiLSTM. Additionally, I was only able to train these models for a limited number of epochs.

[abhisheks008]

@abhisheks008 Due to resource constraints, including limited GPU allocation, frequent runtime disconnects across multiple accounts, and the substantial size of the dataset, I could only implement two models: CNN and BiLSTM. Additionally, I was only able to train these models for a limited number of epochs.

Any other approach for this project?

[manishh12]

@abhisheks008 Due to resource constraints, including limited GPU allocation, frequent runtime disconnects across multiple accounts, and the substantial size of the dataset, I could only implement two models: CNN and BiLSTM. Additionally, I was only able to train these models for a limited number of epochs.

Any other approach for this project?

Yes, there are algorithms that I know of, but they are machine learning algorithms like support vector machine (SVM) or multinomial naive Bayes. If you want, I can implement one of these algorithms.

[abhisheks008]

Go ahead with those models @manishh12

[manishh12]

Go ahead with those models @manishh12

@abhisheks008 I've implemented the MNB model and updated the readme. Please review it.

[abhisheks008]

@manishh12 the project folder name should be Website Classification, no underscore will be there.

[manishh12]

@manishh12 the project folder name should be Website Classification, no underscore will be there.

@abhisheks008 Kindly Review it.

[abhisheks008]

@manishh12

[abhisheks008]

Images are not visible.

[manishh12]

Images are not visible.

@abhisheks008 Sorry, I forgot to update the link after renaming. It's now displaying correctly. Please review it.