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peterwhycs/README.md

Hello, GitHub! πŸš€

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

Welcome to my space! I’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.

πŸŽ“ 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.

πŸ’Ό 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.

πŸ› οΈ 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

🌱 I’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.

πŸ“« How to reach me:

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


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  1. T-BEAR T-BEAR Public

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

    Python 12 2