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  1. Sentiment_analysis Sentiment_analysis Public

    We employed a Long Short-Term Memory (LSTM) neural network to analyze sentiments in a Twitter dataset. The objective was to categorize tweets as either positive or negative based on their content.

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  2. DeepAutoEncoders- DeepAutoEncoders- Public

    applying-vanilla-and-convolutional-autoencoder-to-Mnist-dataset

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  3. DeepImageGenerator DeepImageGenerator Public

    using Convolutional Autoencoder to generate images

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  4. signal-processing-compressive-sensing signal-processing-compressive-sensing Public

    applying compressive sensing algorithm to reconstruct signal from random selections .

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  5. Graph-machine-learning Graph-machine-learning Public

    Node classification using Node2Vec method for karate_club dataset

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  6. Chest-X-Ray-classification- Chest-X-Ray-classification- Public

    new dataset for medical application consisting of different type from medimeta , you can use the mnist type or the original type, applyinig multiclass classification using pytorch and oop model

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