VideoQuest
A video search engine with a GUI utilizing MongoDB, Neo4j, and MySQL for data storage.
It features video indexing, relationship management, user authentication, sentiment analysis for comments, and personalized video recommendations.
I'm Tanish Pagaria, a pre-final year B.Tech. student at IIT Jodhpur, pursuing Artificial Intelligence and Data Science. I am passionate about leveraging technology to solve real-world problems.
I have worked primarily in the domain of software development, with a strong emphasis on machine learning and data-driven solutions. My focus lies in tackling complex problems, developing predictive models, and harnessing data to derive actionable insights.
View ResumeA video search engine with a GUI utilizing MongoDB, Neo4j, and MySQL for data storage.
It features video indexing, relationship management, user authentication, sentiment analysis for comments, and personalized video recommendations.
A machine learning pipeline to classify logos from teams in the top 5 football leagues.
The dataset was generated by augmenting single images for each team. The classification employed various machine learning algorithms, such as Convolutional Neural Networks and SVM. The tech-stack includes Python, Scikit-Learn, PyTorch, TensorFlow, Pandas, Matplotlib, Pillow, and Streamlit.
Water Quality Prediction, part of the Intel OneAPI AI Hackathon, aimed to assess freshwater sustainability.
The project developed a binary classification model using TabNet ensembling, achieving 87.39% accuracy and a 0.81786 F1 score. Handling a large dataset with missing values was made effective through detailed data analysis. The tech-stack involved Python, Intel AI Analytics Toolkit, Scikit-Learn, PyTorch, and Pandas.
Programming Languages: Python, C/C++, Java
Web Development: Django, HTML, CSS, JavaScript, ReactJS
Data Science: Pandas, Matplotlib, Seaborn, PyTorch, Scikit-Learn
Technologies: PyQt5, PyMongo, SQL, Git/GitHub, Ubuntu