Github, Pyspark, Apache Spark, AWS CloudWatch, AI ML, Jenkins, Linux, Terraform, Bitbucket, Python, AWS, Generative AI, AWS EMR

Machine Learning, Pandas, Docker, Spark, Sql, Python, Kubernetes, Generative AI, LLM technologies

Tensorflow, Pytorch, Docker, Map, Python, AWS, Gcp, Cloud, MLops, Opencv, Azure, Kubernetes, Computer Vision, SAM, U-Net, PRECISION, ResNet, CLIP, IoU, MobileNet, recall, Faster R-CNN, DETR, ViT, EfficientNet, F1, Mask R-CNN, YOLO, Swin Transformer

Machine Learning, Deep Learning, Data Science, Python, Generative AI, explainable AI, Forecasting, ML libraries, model evaluation, Statistical Modeling, time-series analysis, cloud-based ML platforms

Sql, MLops, Azure Cloud, Databricks, Python, Azure DevOps, Feature pipelines, End-to-end ML lifecycle, CI CD CT pipelines, Enterprise Feature Store, lineage, reproducibility, MLflow, Unity Catalog, Feature engineering, Model Registry, Jobs, Delta Lake, ML governance, observability, Databricks Workflows

Java, Microservices, MLops, Docker, Databricks, Rest Apis, Kubernetes, Python, MLflow, GenAIOps, SageMaker, Kubeflow

Pandas, XGBoost, Spark, Databricks, Python, SHAP, scikit-learn, LightGBM, MLflow, model observability, LIME, Delta Lake, explainability frameworks, drift detection

Java, Python, Scala, Deployment practices, ML lifecycle

Databricks, Java, Microservices, Golang, Machine Learning, AWS, Python, Scala, Spark, Statistics, GenAI, MLFlow, LangChain, distributed data processing frameworks, LangGraph

Excel, Python, ML algorithms, ML models