Pinned Loading

1. Detecting-Machine-Generated-TextDetecting-Machine-Generated-TextPublic

   The findings of this research reveal several intriguing disparities between human and AI text generation. I demonstrated that these differences could be successfully utilized by classifiers to dist…

   Jupyter Notebook 8 1

2. Watermarking-Algorithm-Analysis-on-BART-Model-using-CNN-DatasetWatermarking-Algorithm-Analysis-on-BART-Model-using-CNN-DatasetPublic

   Jupyter Notebook 3

3. StockGPTStockGPTPublic

   A Python script to analyze financial news and publish them on a Telegram channel.

   Python 17 1

4. Predicting-YouTube-Dislikes-using-Machine-LearningPredicting-YouTube-Dislikes-using-Machine-LearningPublic

   I used Catboost for training a model on the numerical features of every YouTube video (e.g., the number of views, comments, likes, etc.) along with sentiment analysis of the video descriptions and …

   Jupyter Notebook 9

5. Automated-Design-of-Symmetric-Autoencoders-Using-Genetic-AlgorithmsAutomated-Design-of-Symmetric-Autoencoders-Using-Genetic-AlgorithmsPublic

   This project presents a novel approach for optimizing the architecture of symmetric, undercomplete autoencoders for dimensionality reduction using a genetic algorithm.

   Jupyter Notebook 1 1

6. Word-Clouds-With-Sentiment-Analysis-of-the-Most-Recent-TweetsWord-Clouds-With-Sentiment-Analysis-of-the-Most-Recent-TweetsPublic

   Downloaded tweets from the most popular news agencies and extract keywords from them. In the next steps, I plotted a word cloud and did a sentiment analysis for tweets that have the keywords.

   Jupyter Notebook 5