Machine Learning, cloud platforms and services for deploying AI solutions, data preprocessing and feature engineering

Deep Learning, Numpy, Decision Trees, Pandas, MLops, Pytorch, Gcp, Clustering, Azure, Python, AWS, Etl, LangChain, vector search, embeddings, agentic AI, data pipelines, tool calling, LLMOps, CNNs, prompt engineering, LangGraph, ensembles

data engineering , Machine Learning, Algorithms, Pandas, Data structures, Python, Standard ML algorithms, LLM-based solutions, Software design principles

containerization , Hadoop Ecosystem, Java, Tableau, Data Visualization, Kafka, Machine Learning, Power Bi, MySQL, Bi Tools, Scala, PostgreSQL, Flume, Big Data Technologies, Shell scripting, Data Modeling, RDBMS, Google Cloud, AWS, Distributed Systems, Python, Azure, Statistical Analysis, Jenkins, Devops Tools, MongoDB, Spark, large-scale application development, CI CD pipelines, R, NoSQL databases

Apis, Performance Monitoring, Version Control, Gcp, MLops, Azure, Python, Statistical Analysis, Machine Learning Algorithms, AWS, data preprocessing, cloud platforms, production-ready ML pipelines, model evaluation, deep learning techniques, feature engineering, model lifecycle management, model optimization, hyperparameter tuning

data engineering , Ml, FastAPI, Kubernetes, Python, AWS EKS, Nlp, Celery, Sqlalchemy, confidence calibration techniques, Airflow, Claude API, vector database, Ai, Pydantic, LLM output validation frameworks, embedding models, Weaviate, pgvector, semantic search, data ingestion pipelines, Pinecone, LLM evaluation frameworks, prompt engineering