Machine Learning sits at the heart of modern AI systems. I work with organizations to design, train, and deploy ML models that solve real business problems — from predictive analytics and recommendation engines to anomaly detection and demand forecasting.

Core Capabilities

• Supervised Learning — Classification, regression, ensemble methods, gradient boosting
• Deep Learning — Neural networks, transformers, CNNs, transfer learning
• MLOps & Pipelines — Model training, validation, deployment, monitoring, and retraining workflows
• Feature Engineering — Data preprocessing, feature stores, dimensionality reduction
• Platforms — SageMaker, Vertex AI, Azure ML, Databricks, MLflow

Great ML isn’t just about algorithms — it’s about clean data, robust pipelines, and continuous monitoring. Discover my machine learning insights below.