Deep Learning, Machine Learning, Programming, Deployment, N

Tensorflow, Pytorch, Keras, Python, Statistical Analysis, image processing algorithms, machine learning pipelines

Machine Learning (ML), Artificial Intelligence (AI), Hadoop, Pyspark, Autosys, Sql, Angular, React, Spark, Python, Data Architecture, Metadata Management, DevOps practices, Flink, Copilot AI tool, Distributed data processing, Model context, Platform modernization, Performance optimization, Production support models, CI/CD pipelines, Agentic frameworks and flows, Enterprise controls, Data quality frameworks, Generative AI models, Protocol MCP

Pyspark, Apache Spark, Data Warehousing, Kafka, Dimensional Modeling, Sql, ELT, Apache Airflow, Git, Gcp, Terraform, Docker, Databricks, Azure, Python, Kubernetes, AWS, Etl, Apache Iceberg, Generative AI, Delta Lake, Apache Hudi, Large Language Models

Python, Tensorflow, MLops, AWS, Pytorch, FastAPI, Kubernetes, Azure, Gcp, Docker, Flask, Milvus, Hugging Face transformers, vector databases, Pinecone

Tensorflow, Numpy, Pytorch, Pandas, Keras, Python Programming, Prompt engineering, Koalas, Horovod, LayoutLM, DDP, Generative AI techniques, BERT

PostgreSQL, Kafka, Spring Boot, Microservices, Java 8, Docker, MySQL, Oracle, AWS, Hibernate, Sql, Rabbitmq, Git, Gcp, Rest Apis, Azure, Jpa, Kubernetes, pgvector, vector databases, Pinecone, LLM APIs, Spring AI, ChromaDB, LangChain, generative AI, prompt engineering, LangChain4j, RAG, Weaviate