Dropout Prediction System
Summary
Developed a machine learning system to predict student dropout risks using educational data, focusing on model training, preprocessing, evaluation, and Flask deployment planning.
Daniel Abiodun
Machine Learning Engineer & Automation and Embedded Systems Expert.
Mowe, NG.About
Motivated AI/ML enthusiast and aspiring Full-Stack Developer with hands-on experience in Python, machine learning, OpenCV, and web application deployment using Flask. Passionate about leveraging data-driven solutions to build intelligent systems, actively applying a builder's mindset to solve real-world problems, particularly within robotics, automation, and critical African challenges. Proven ability to rapidly acquire new technical skills and drive innovative project development from concept to deployment.
Languages
English
Yoruba
Education
Secondary School
Mowe, Ogun State, Nigeria
Secondary School Certificate (SSCE)
General Studies
Certificates
100 Days of AI Bootcamp
Issued By
Max Haining
Skills
Technical Skills
Python Programming, Machine Learning Fundamentals, OpenCV & Image Processing, HTML & CSS, Flask (Web App Deployment), Arduino & Embedded Systems, Data Analysis, API Integration, Git & GitHub Basics, Graphics Design.
Tools & Platforms
VS Code, Google Colab, Jupyter Notebook.
Soft Skills
Research & Problem Solving, Communication, Creativity, Team Collaboration, Adaptability, Technical Writing & Editing.
Interests
Artificial Intelligence & Machine Learning
Robotics & Automation
Forex Trading Systems
Mobile App Development
Technical Content Creation
Projects
Drone Prototype Development
Summary
Designed and developed a personal drone prototype, exploring hardware integration, electronics, and embedded systems concepts to build a functional model.
WhatsApp Auto-Reply Chatbot
Summary
Conceptualized and planned a WhatsApp chatbot designed for automated customer replies, inquiry handling, and seamless API integration workflows.
AI & Public Health Research Concepts
Summary
Researched and conceptualized machine learning applications for healthcare and public health problem-solving, utilizing locally simulated datasets to explore practical solutions.