Skills: AI, ML, Backend, Cybersecurity

AI / Machine Learning

• Autonomous Agents
• Supervised Learning
• Deep Learning
• Unsupervised Learning & Recommender Systems
• Foundational and Applied Machine Learning techniques
• Data Structures and AI Algorithms
• Practical implementation and deployment using Python and modern ML libraries
• Hands-on experience implementing Machine Learning models with real-world datasets to solve problems
• AI Ethics + Quantifying Fairness and Bias
• Machine Learning algorithms and their mathematical foundations
• Evaluate and optimize models for real-world applications
• Communicate findings and justify design decisions in machine learning pipelines

• Platforms: Google Colab, LiquidMetal AI, Vercel
• Libraries: NumPy, pandas, scikit-learn, TensorFlow, matplotlib, PyTorch