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Discipline Module 2 · Descriptive Data Analysis

Dimensionality Reduction Techniques

Workload
15h
Professor Profª. Drª. Helen de Cássia Lima PhD in Computer Science with experience in NLP and data mining.
Syllabus

Data types. Data quality. Preprocessing. Similarity and dissimilarity measures. File formats and data storage. Data cleaning and preparation. Data organization. Aggregation and grouping operations. Dimensionality reduction. Feature selection.

Content
  • Data types
  • Data quality
  • Preprocessing
  • Similarity and dissimilarity measures
  • File formats and data storage
  • Data cleaning and preparation
  • Data organization
  • Aggregation and grouping operations
  • Dimensionality reduction
  • Feature selection
Core Bibliography
  • Tan, P.-N., Steinbach, M., Karpatne, A., & Kumar, V. (2018). Introduction to Data Mining (2nd Edition) (2nd ed.). Pearson.
  • Zaki, M. J., & Jr., W. M. Data Mining and Machine Learning: Fundamental Concepts and Algorithms. Cambridge University Press, 2020. http://www.dataminingbook.info/
  • McKinney, Wes. Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython. 3. ed. O'Reilly Media, Inc., 2023.
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