Data Preprocessing

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• AI Governance / Algorithm Administration
  • Data Science / Data Governance
    • Benchmarks
    • Data Preprocessing
      • Feature Exploration/Learning
      • Data Quality ...validity, accuracy, cleaning, completeness, consistency, encoding, padding, augmentation, labeling, auto-tagging, normalization, standardization, and imbalanced data
    • Bias and Variances
    • Master Data Management (MDM)
      • Managed Vocabularies
      • Datasets
    • Privacy in Data Science
    • Data Interoperability
    • Excel - Data Analysis
• Development ...AI Pair Programming Tools ... Analytics ... Visualization ... Diagrams for Business Analysis
• Hyperparameters
• Evaluation ... Prompts for assessing AI projects
  • Evaluation - Measures
• Train, Validate, and Test
• Python ... Generative AI with Python ... Javascript ... Generative AI with Javascript ... Game Development with Generative AI
• Scale ... data collection, curation, labeling, and annotation
• Sklearn.preprocessing
• The Passenger Screening Kaggle challenge 1st place solution was won in part due to data preparation/generation.
• Data Pre Processing Techniques You Should Know | Maneesha Rajaratne - Towards Data Science
• Machine Learning(ML) — Data Preprocessing | Raji Adam Bifola
• Most Influential Data Preprocessing Algorithms | S. García, J. Luengo, F. Herrera
• How to fix an Unbalanced Dataset | Will Badr - Amazon Web Services
• Creating and Using Datasources | Amazon Web Services
• Jon Tupitza Famous Jupyter Notebooks:
  • Data Preparation 01
  • Data Preparation 02
• The COVID Tracking Project - software used

Article

Time-Series Data

• Backtesting
• Time-based Algorithms
• A Comparison of Time Series Databases and Netsil’s Use of Druid | Netsil
• Microsoft announces the general availability of Azure Time Series Insights | Ryan Waite - Microsoft
• Top 10 Time Series Databases | Outlyer

Categorical Variables

• All about Categorical Variable Encoding | Baijayanta Roy - Towards Data Science

Categorical variables require special attention in regression analysis because, unlike dichotomous or continuous variables, they cannot by entered into the regression equation just as they are. Instead, they need to be recoded into a series of variables which can then be entered into the regression model. There are a variety of coding systems that can be used when recoding categorical variables. Coding Systems for Categorical Variables In Regression Analysis | UCLA institute for Digital Research & Education Statistical Consulting