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  2. INF2-FDS: Informatics 2 - Foundations of Data Science
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  4. INF2-FDS: S1 Week 9 - Dealing with high dimensions

INF2-FDS: S1 Week 9 Lab

In your lab session, work with a partner through the Jupyter notebook S1 Week 08: Principal Components Analysis, which is available from this Github repository https://github.com/Inf2-FDS/FDS-S1-08-pca.git

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Book traversal links for INF2-FDS: S1 Week 9 Lab

  • INF2-FDS: S1 Week 9 Workshop
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  • INF2-FDS: S1 Week 10 - Randomness, sampling and simulation

Navigation links

  • INF2-FDS: Course team
  • INF2-FDS: Schedule
  • INF2-FDS: Course Materials
    • INF2-FDS: S1 Week 1 - Introduction and Data
    • INF2-FDS: S1 Week 2 - Descriptive statistics
    • INF2-FDS: S1 Week 3 - Exploratory data analysis, data communication and visualisation
    • INF2-FDS: S1 Week 4 - Data Ethics, Data Scraping and statistical relationships
    • INF2-FDS: S1 Week 5 - Introduction to supervised learning - Nearest Neighbours
    • INF2-FDS: S1 Week 6 - Linear models
    • INF2-FDS: S1 Week 7 - Coursework 1
    • INF2-FDS: S1 Week 8 - Multiple regression
    • INF2-FDS: S1 Week 9 - Dealing with high dimensions
      • INF2-FDS: S1 Week 9 Workshop
      • INF2-FDS: S1 Week 9 Lab
    • INF2-FDS: S1 Week 10 - Randomness, sampling and simulation
    • INF2-FDS: S1 Week 11 - Estimation and confidence intervals
    • INF2-FDS: S2 Week 1 - Hypothesis testing and A/B testing
    • INF2-FDS: S2 Week 2 - Logistic regression
    • INF2-FDS: S2 Week 3 - Introduction to unsupervised learning - K-means
    • INF2-FDS: S2 Week 4 - Ethical and legal issues in supervised learning
    • INF2-FDS: S2 Week 5 - Regression and inference
    • INF2-FDS: S2 Week 6 - Software engineering for data science
    • INF2-FDS: S2 Week 8 Project writing workshop
    • INF2-FDS: Revision
  • INF2-FDS: Labs
  • INF2-FDS: Workshops
  • INF2-FDS: Resource List
  • INF2-FDS: Assessment
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