Sql, Tensorflow, MLops, Gcp, Pytorch, Docker, Spark, Azure, Python, Kubernetes, AWS, Observability and Monitoring, Scikit-learn, API and Microservices Architecture, Vector Databases, AI Evaluation Frameworks, Feature Stores, Reinforcement Learning concepts, Model Deployment, Agentic AI Systems, Experiment Tracking

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

Python, Sql, Tensorflow, MLops, AWS, Pytorch, Kubernetes, Azure, Gcp, Docker, Spark, API and Microservices Architecture, AI Evaluation Frameworks, Observability and Monitoring, Feature Stores, Scikit-learn, Agentic AI Systems, Reinforcement Learning concepts, Vector Databases, Experiment Tracking, Model Deployment

Tensorflow, Pytorch, Gcp, Azure, Kubernetes, Python, AWS, MLOps tools, Scikit-learn

Machine Learning, Amazon CloudWatch, Tensorflow, Pytorch, MLops, AWS CloudFormation, AWS, Generative AI, AWS Step Functions, scikit-learn, Model Observability, Amazon SageMaker, Amazon Bedrock

triton , Pytorch, FastAPI, Kubernetes, Python, Docker, Restful Apis, Sagemaker, ML technologies, document databases, TensorRT

S3, Sql, Lambda, Pytorch, Docker, Kubernetes, Python, AWS, OR-Tools, reinforcement learning, SageMaker, CVXPY, Gurobi

Video Codecs, Cuda, Pytorch, Python, Computer Vision, Git, video processing pipelines, model evaluation frameworks, inference optimization, MLOps tools, MLflow, streaming technologies, deep learning frameworks, attention mechanisms, PEFT, continuous experimentation infrastructure, CNNs, GPU-based training, LoRA, Weights Biases, Transformers

snowflake , Spark, Sql, Databricks, Kafka, Machine Learning, MLops, Data Science, Python, LLMs, Airflow, Probabilistic modeling, Tree-based models, Feature engineering, Generative AI, Transformers

Pytorch, Azure, Aws