Fundamentals of Data Science: Transforming Data into Action

  • Data
  • Information
  • Knowledge
  • Intelligence
  • Action


  • Statistical analysis
  • Regression
  • Classification
  • Clustering
  • Time series analysis
  • Anomaly detection
  • NLP
  • Distributed ML
  • Graph analysis
  • Recommender systems
  • Neural networks / Deep learning

Data Science Pipeline

  1. Planning
  2. Acquisition
  3. Preparation
  4. Exploration
  5. Modeling
  6. Delivery
  7. Maintenance

Author: Ednalyn C. De Dios

I’ve always been enamored with code and I love data science because of its inherent power to solve real problems. Having grown up in the Philippines, served in the United States Navy, and worked in the nonprofit sector, I am driven to make the world a better place. I have started and participated in numerous campaigns that aim to reduce domestic violence and child abuse in the community.

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