Svm, XGBoost, Python, Decision Trees, Clustering, MLops, Restful Apis, Agent reasoning patterns, Prompt engineering, Feature selection, scikit-learn, RAG systems, Data preprocessing, Conversation analytics, AI system observability frameworks, LLM conversational AI systems, Feature engineering, semantic search, AWS Sagemaker, LangChain, CrewAI, Vector databases, LightGBM, Ensemble models, Regression, Statistical Modeling, Agent frameworks, Context optimization

Java, Docker, Kubernetes, Python, TFX, AWS SageMaker, Kubeflow, Google Vertex AI, Go, MLflow, Metaflow

Apache Spark, Sql, Pytorch, Docker, Databricks, Python, Model Serving Frameworks, AWS ecosystem, SHAP, scikit-learn, MLflow, TF Serving, ONNX, Cloud Platforms, LIME, Kubeflow, MLOps tools, Model Explainability tools

Apis, MLops, LangChain, Generative AI, Prompt engineering, orchestration tools, LLMs, airflow, custom model building, Agentic AI architecture, MLflow, Training, MCP server building, crewai, cloud agnostic model evaluation, prefect, Transformers, OpenAI, Kuberflow, Cohere, LlamaIndex

Tensorflow, Git, Pytorch, MLops, Docker, Flask, FastAPI, Python, Kubernetes, AWS, Airflow, vector databases, embedding models, Sagemaker, Streamlit

Sql, Git, Pandas, Gcp, Pytorch, Docker, Spark, Azure, Kubernetes, Python, AWS, Prefect, Airflow, Scikit-learn, MLflow, dbt, Kubeflow, BentoML

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

Sql, ELT, Tensorflow, Hadoop, Tableau, MLops, Power Bi, Etl, AWS, Pytorch, Kubernetes, Python, Azure, Docker, Gcp, Spark, Scikit-learn, Airflow, dbt