https://github.com/sreecharanv/tokenization-and-categorization-using-ocaml-a-lexical-analysis-approach

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, categorizing tokens, and printing them with their respective categories. Key functions include tokenize, is_alnum, is_punctuation, and print_tokens.

lexical-analysis lexical-analyzer ocaml ocaml-program tokenization

Last synced: 15 Mar 2025

https://github.com/sreecharanv/building-a-language-understanding-and-question-answering-system-from-open-ended-trivia-data

This project uses BERT to build a QA system fine-tuned on the SQuAD dataset, improving the accuracy and efficiency of question-answering tasks. We address challenges in contextual understanding and ambiguity handling to enhance user experience and system performance.

adaptive-learning bert bert-model finetuning-large-language-models jeopardy-trivia machine-learning machinelearning natural-language-processing natural-language-understanding nlp-machine-learning qa question-answering questions-and-answers squad

Last synced: 23 Mar 2025

https://github.com/sreecharanv/prolog-based-graph-traversal-bfs-implementation

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 undirected graphs with extensive test cases.

bfs-algorithm bfs-search graphtraversal prolog prolog-programming-language

Last synced: 23 Mar 2025

https://github.com/sreecharanv/visualizing-current-data-science-salary-trends-key-insights-for-job-seekers

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 professionals understand salary patterns in the data science field.

datascience datavisualization insight-data-science jobseekers matplotlib pyplot python seaborn-plots trendanalysis visualize-data

Last synced: 23 Mar 2025

https://github.com/sreecharanv/generating-realistic-and-diverse-textual-movie-reviews-with-imdb-dataset-leveraging-deep-learning

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 evaluated for coherence and diversity, showcasing GPT-2's potential in automated text generation.

deep-learning deep-neural-networks gpt-2 large-language-models machine-learning movie-reviews natural-language-processing text-generation

Last synced: 23 Mar 2025

https://github.com/sreecharanv/improving-cifar-10-image-classification-with-diverse-architectures-using-ensemble-learning

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-model approaches, achieving superior classification performance.

cifar10-classification cnn-classification computervision ensemble-learning ensemble-machine-learning ensemble-model imageclassification machine-learning machine-learning-algorithms python rnn-model transfer-learning vgg16 vgg16-model

Last synced: 23 Mar 2025

https://github.com/sreecharanv/portfolio

Last synced: 23 Mar 2025

https://github.com/sreecharanv/utilizing-multinomial-naive-bayes-for-enhanced-movie-genre-classification-and-analysis

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 improve content recommendation systems through accurate genre prediction.

artificial-intelligence classification classifier-model genre-classification machine-learning moviegenredetection multinomial-naive-bayes naive-bayes-classifier netflixdata prediction-model

Last synced: 23 Mar 2025