An analysis of the systemic impact, on the Web, of AI systems, and in particular ones based on Machine Learning models, and the role that Web standardization may play in managing that impact

Analyze WhatsApp chats with ML & Generative AI to reveal mood trends, apology/gratitude frequency, personas, and conversation insights. Built with Python, Streamlit, Pandas, and LLMs. Visualize your chat history like never before!

An AI driven platform which can analyze and predict crop diseases and provide future medication recommendation for the disease

Slash Engine - Web based UI (Interface) for your locally hosted AI models.

IT Bootcamp Final Exam Project: Delve into the world of data science with this exam. Explore consumer dispute data, apply machine learning models, and analyze sentiment to solve real-world financial service challenges.

Fin-AI-lytics is an AI financial advisor for stocks and portfolio management, built with Python-Streamlit, Firestore, ML models, and APIs like YFinance and Alphavantage. It provides a user-friendly walkthrough for beginners, real-time stock analysis, portfolio optimization, and interactive financial tools with data visualizations.

A repository containing Jupyter Notebooks for neural network models, optimization algorithms, regularization techniques, and classification tasks with real-world datasets.

AIJURIST is an AI-powered legal predictor that uses advanced machine learning algorithms to predict the chances of winning a legal case based on provided case descriptions and evidence.

Car Predictive Maintenance uses machine learning to analyze vehicle data and predict potential failures, enabling timely repairs, reducing breakdowns, and extending vehicle lifespan.

Learn ML models in an interactive way, by seeing which ML models suits what kind of data and approximate speed of training.

An in-depth exploration of logistic regression models, including data cleaning, model building, and performance evaluation on various datasets.

Built a fake news classification system using NLP and ML on a Kaggle dataset of 40,000+ articles. Preprocessed text, applied TF-IDF, and trained Naive Bayes, Logistic Regression, and Linear SVM. Achieved 99.3% accuracy with Linear SVM. Includes evaluation and visualizations.

This study develops a CNN-LSTM model for Human Activity Recognition using accelerometer and gyroscope data. Achieving over 95% accuracy, it combines LSTM's temporal capabilities with CNN's spatial features.

Student performance prediction models

An automated, collaborative ethical bias auditing platform for ML models. Demo:https://youtu.be/8mE_vLP9TYc

Proyecto para el Hackathon Innovation Challenge Microsoft, utilizando datos públicos para mejorar la gestión del conocimiento en salud global. Facilitamos la colaboración interinstitucional y decisiones basadas en evidencia entre agencias, empresas y organizaciones.

Car Predictive Maintenance uses machine learning to analyze vehicle data and predict potential failures, enabling timely repairs, reducing breakdowns, and extending vehicle lifespan.