Artificial Intelligence

Artificial Intelligence is the art and science of teaching machines to learn, reason, and create. It’s the engine that transforms raw data into intelligent action, enabling systems to understand complex patterns, make predictions, and generate innovative solutions. My work focuses on building and deploying these intelligent models to solve real-world problems.

Key Technologies & Frameworks:

TensorFlow: The industry-leading deep learning framework for building and training neural networks, from computer vision to natural language processing.

Scikit-learn: The go-to library for classical machine learning, providing robust and efficient tools for classification, regression, clustering, and data preprocessing.

MLflow: MLOps platforms for managing the entire machine learning lifecycle, from experiment tracking and model versioning to deployment and monitoring.

Arize AI: A platform for observability and monitoring of machine learning models, ensuring they perform as expected in production environments.

Qdrant: For managing and querying high-dimensional vector data, essential for applications like semantic search and recommendation systems to manage embedding.

LlamaIndex: A framework for building applications with large language models, enabling efficient data retrieval and processing.

Ollama: A platform for deploying and serving large language models, providing a user-friendly interface for interacting with AI models.

Key Projects:

Comprehensive Recommender System Guide: A detailed guide on building recommender systems, covering collaborative filtering, content-based filtering, and hybrid approaches. It includes practical examples and code implementations.