Python Programming, Generative AI, RAG and embeddings, Prompt Engineering

Neural network architectures, Generative AI, Deep learning frameworks, Image processing techniques

Sql, Tensorflow, Pandas, Pytorch, Spark, Splunk, Python, Monitoring for data and model drift, Scikit-learn, MLflow, Model versioning, Flink, LLM-based agents, Agentic AI, CI/CD for ML, Ciena Blue Planet UAA

Machine Learning, Nlp, Docker, Python, AWS, Databases, Sql, Deep Learning, Gcp, Rest Apis, Azure, RAG agentic AI, vector search, embeddings, pgvector, Qdrant, vector databases, Pinecone, CI CD, model evaluation, backend systems, retrieval, experimentation, AI APIs, Generative AI, LLMs, scalable application architecture, Monitoring, prompt engineering, performance optimization, Milvus, Weaviate, production engineering practices

Tensorflow, Natural Language Processing, Generative Adversarial Networks, Python, Pytorch, Machine Learning Algorithms, Text-to-Image, Conditional GANs, Latent Diffusion, Draping algorithms, Deep Neural Networks, InPainting, Image-to-Image, Feature engineering, Speech-to-Text, Data pre-processing, Text-to-Speech, Stable Diffusion, Texture Mapping, Fabric simulation, Transformers