Python, LangChain, Azure OpenAI APIs, Chroma, Vector databases, FAISS, Ai, OpenAI, Pinecone, LlamaIndex

Tensorflow, Numpy, Pandas, Pytorch, Python, MLOps practices, AWS SageMaker, Statistical libraries, Scikit-learn, Jupyter

Hypothesis Testing, Sql, Tensorflow, Pytorch, Decision Trees, Arima, Keras, Python, Statistical Analysis, KubeFlow, exponential smoothing, support vector machines, Great Expectations, Z-Test, probabilistic graph models, T-Test, Regression, MXNet, Evidently AI, CNTK, ARIMAX, Sci-Kit Learn, BentoML

Machine Learning, Artificial Intelligence, Prometheus, Grafana, Sql, MLops, Docker, Azure, Kubernetes, Python, AWS, Generative AI, LLMOps, Data Bricks, Agentic AI, Prompt Engineering, Large Language Models

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

Github, Apis, Tensorflow, Numpy, Git, Pandas, MLops, Pytorch, Docker, Azure, Kubernetes, Python, AWS, agentic architecture, GenAI, scikit-learn, LLMOps, Llm, distributed services, infrastructure as code

graph databases , probability , Machine Learning, Cloud Security, Sql, Deep Learning, Cuda, Tensorflow, MLops, Pytorch, Terraform, Docker, Python, Kubernetes, Generative AI, Vector databases, MLflow, calculus, Kubeflow, Econometrics

Machine Learning, Apis, Natural Language Processing, Microservices, Devops, Data Privacy, Python, CI CD, cloud environments, responsible AI, AI services, Security, model-serving pipelines, large language models, data ingestion