AWS, Tensorflow, Pytorch, Gcp, Docker, Azure, Kubernetes, Python, Scikit-learn

Lambda, S3, Cloudformation, MLops, Kinesis, Terraform, Docker, Databricks, Python, AWS, Airflow, ML infrastructure, Step Functions, MLflow, EKS, SageMaker, GitHub Actions

Python, Linux, Docker, AWS SageMaker, SageMaker SDK, ML Concepts

MLops, Data DevOps

containerization , Azure ML, Scripting Language, Scala, Pyspark, Terraform, Docker, Distributed Systems, Arm, Python, Kubernetes, Etl, data architectures, DevOps practices, infrastructure automation, Data Analytics tools, ML workflows, CI CD pipelines, MLOps tooling, Bicep, feature engineering

Machine Learning, Pyspark, Pytorch, Docker, Python, AWS, Azure DevOps, Sklearn, Automated Testing, Git, MLops, Databricks, Kubernetes, MLflow, GitHub Actions, Experiment tracking, Observability, Monitoring, Model registries, Model drift analysis, Governance, versioning, Lakehouse, CI/CD, Evidently AI

Machine Learning, MLops, Databricks, Model Monitoring, Model Deployment