Adeyemi Adedoyin Simeon

Analysis of Air Pollution prediction and time-series forecast of PM2.5 Pollutant using Machine Learning Algorithms (SVM, Decision Tree and Random Forest) and Deep Learning Algorithms (CNN, Bi-LSTM). Also considered for improved performances is random search hyper-parameter tuning using Ray-Tune with HyperBand Scheduler strategy.

CLIENT: A user-facing `Streamlit` client application for interacting with custom built Stock Adviser and Wiki Search AI Agent (built using Agno Multiagentic framework) implemented using Streamlit. The demo AI Agent, implemented using Agno Agentic Framework, equiped with yfinance and wikipedia tools that can provide stock data, STOCK analysis...

A modular, notebook-first GitHub Copilot framework for developing reproducible, publication-quality machine learning research with explainable AI, rigorous statistical validation, experiment tracking, and journal-ready artifacts.

Beginner-friendly Machine Learning workshop: classify lung cancer risk from survey data using Decision Tree, Random Forest, and Naive Bayes in Python.

A complete ML-based app for machine predictive maintenance. Predicts Remaining Useful Life of a machine, classifies machine status as healthy, warning or critical, etc. Involves model development (LSTM, Random Forest, Isolation Forest), Backend with FastAPI, frontend with React.

A simple RAG-powered agentic solution. Implemented using LangChain agent, Groq Llama model, FAISS vector-store, HuggingFace Embedding, PyPDF loader, RecursiveCharacterTextSplitter, Docker, FastAPI for backend, uv package manager, among others.