About

Bio

A Data Engineer with background in Data Science, Computer Science, Software Engineering, Data Modeling. Also familiar with web application development.

Data Engineering skills and tools

• Languages: Python, SQL, Ruby, Java, PHP
• Databases: Postgres, MySQL, MongoDB, Redis, Cassandra, AWS RDS, RedShift
• Batch ETL: Python, SparkSQL
• Streaming ETL: Kafka, Spark Streaming, AWS Kinesis, Lambda
• Workflow Management: Airflow, AWS Glue

DE Portfolio

• Tweet Sentiment Analysis Dashboard on AWS
• Kafka Spark Streaming on Docker

Data Science skills and tools

• Languages: Python, SQL, MATLAB, Octave
• Deep Learning: TensorFlow
• Machine Learning: scikit-learn, pandas, numpy
• Deployment: AWS Sagemaker, Docker, Kubernetes, GCP Container Engine
• Visualization: AWS QuickSight

DS Articles

• Machine Learning Articles
• Deep Learning Articles

DS Portfolio

• Google Cloud & NCAA ML Competition 2020-NCAAM, Time series forecasting.
• Flower Classification with TPUs, Use TPUs to classify 104 types of flowers

Other Skills and tools

• Modeling: ICONIX Process(Use case driven object modeling), UML Modeling(Business, Architecture, DB),
• CI/CD: Github Actions
• Computer Science & Algorithm: Google foobar challenge lv4(be going on)
• Web application developing: Full-stack (more familiar with backend)
• OS: Linux, FreeBSD

Certifications

• Deep Learning
  • Structuring Machine Learning Projects
  • Neural Networks and Deep Learning
  • Convolutional Neural Networks
  • Sequence Models
  • Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization
• Network Specialist(IPA Certified)
• Class I Information Technology Engineer(IPA Certified)