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šŸ§‘ā€šŸ’» Peter Yuan: Cloud Data Engineer & Machine Learning Practitioner

Welcome to my space! Iā€™m Peter, a seasoned Senior Engineer in Data Engineering with a knack for building and modernizing cloud data platforms and machine learning applications. I'm currently making waves at Slalom Build, where I transform data into actionable insights.

šŸŽ“ What I Do

  • Cloud Data Architecture: Expert in designing scalable, efficient cloud solutions using AWS, Azure, and GCP.
  • Machine Learning: Implementing data models and integrating cutting-edge technologies like OpenAI's ChatGPT and Claude 3.
  • Data Warehousing and Analytics: Developing robust data pipelines that power enterprise-level analytics.

šŸ’¼ Experience Highlights

  • Enterprise Application of LLMs & AI (Entertainment Sector): Developed a ChatGPT-based chatbot for event recommendations, leveraging AWS Lambda for scalability and enhanced performance with Claude 3.
  • Enterprise Data Migration & Analytics (Food Services): Modernized data architecture using MSSQL in AWS RDS, boosting business calculations and analytical capabilities.
  • Enterprise Data Streaming & Warehousing (Telecommunications): Crafted near real-time data streaming solutions, optimizing data processing in Azure environments.

šŸ› ļø Tech Stack

  • AWS: EMR, S3, Athena, Lambda, RedShift, Glue, DynamoDB
  • Languages: Python, Java, SQL
  • Tools: Docker, Kubernetes, DBT, Hadoop, Databricks, Airflow, Kafka
  • Platforms: Microsoft Azure, Google Cloud Platform, Snowflake

šŸŒ± Iā€™m currently learning ...

  • Advanced techniques in AI and machine learning to enhance data interaction and automation.
  • Deepening my expertise in cloud-native technologies and microservices architecture.

šŸ“« How to reach me:

Let's connect and explore how data can drive change in our world!


Peter Yuan's Projects

kaggle icon kaggle

Jupyter notebooks and Python scripts with EDA and submissions for Kaggle challenges and datasets.

t-bear icon t-bear

Detect EEG artifacts, outliers, or anomalies using supervised machine learning.

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