Popular repositories Loading

1. Generating-Realistic-and-Diverse-Textual-Movie-Reviews-with-IMDb-Dataset-leveraging-Deep-Learning Generating-Realistic-and-Diverse-Textual-Movie-Reviews-with-IMDb-Dataset-leveraging-Deep-Learning Public

   This project uses GPT-2 to generate realistic movie reviews from the IMDb dataset. By preprocessing data and fine-tuning the model, we achieved human-like text quality. The model's reviews were eva…

   Jupyter Notebook

2. Tokenization-and-Categorization-using-OCaml-A-Lexical-Analysis-Approach Tokenization-and-Categorization-using-OCaml-A-Lexical-Analysis-Approach Public

   An OCaml-based lexical analyzer that identifies and classifies tokens such as identifiers, operators, punctuation symbols, integer literals, and keywords. The project involves tokenizing input text…

   OCaml

3. Prolog-Based-Graph-Traversal-BFS-Implementation Prolog-Based-Graph-Traversal-BFS-Implementation Public

   An implementation of graph traversal algorithms in Prolog, focusing on breadth-first search (BFS). The project finds the shortest path between nodes in a graph, covering both directed and undirecte…

   Prolog

4. Visualizing-Current-Data-Science-Salary-Trends-Key-Insights-for-Job-Seekers Visualizing-Current-Data-Science-Salary-Trends-Key-Insights-for-Job-Seekers Public

   This project analyzes data science salary trends using a Kaggle dataset. By examining factors like job titles, experience levels, and geographic regions, we provide insights to help job seekers and…

   Jupyter Notebook

5. Utilizing-Multinomial-Naive-Bayes-for-Enhanced-Movie-Genre-Classification-and-Analysis Utilizing-Multinomial-Naive-Bayes-for-Enhanced-Movie-Genre-Classification-and-Analysis Public

   This project uses the Multinomial Naive Bayes classifier to enhance movie genre classification based on metadata such as descriptions and ratings. Utilizing a dataset from Kaggle, it aims to improv…

   Jupyter Notebook

6. Improving-CIFAR-10-Image-Classification-with-Diverse-Architectures-Using-Ensemble-Learning Improving-CIFAR-10-Image-Classification-with-Diverse-Architectures-Using-Ensemble-Learning Public

   This project uses an ensemble of CNN, RNN, and VGG16 models to enhance CIFAR-10 image classification accuracy and robustness. By combining multiple architectures, we significantly outperform single…

   Jupyter Notebook