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Printable Handouts
Navigable Slide Index
- Introduction
- Background (1)
- Background (2)
- Talk structure
- Overview
- Why prepare data? (1)
- Why prepare data? (2)
- Domain knowledge and business objective
- Raw data
- Tools and algorithms
- Modeling objective
- Analytical knowledge
- The 4 stages of data mining
- Proportion of project spent on main activities (1)
- Proportion of project spent on main activities (2)
- Applicability of general data preparation techniques
- A continuing and repeated spiral of activities
- Summary of key points from this section
- What is data preparation?
- Data preparation described
- Data preparation background
- What is data?
- Ideal data: C5
- Ideal data: C5 - data survey
- Selecting data for modeling
- Tools (1)
- Tools (2)
- Techniques (1)
- Techniques (2)
- Introducing information transmission
- Introducing information transmission - disjoint (1)
- Introducing information transmission - disjoint (2)
- Introducing information transmission- Interactions
- Preparing data: Where to represent complexity?
- Information transmission by mode (1)
- Information transmission by mode (2)
- Information transmission by mode (3)
- Signal and noise (1)
- Signal and noise (2)
- Summary of six key points from this section (1)
- Summary of six key points from this section (2)
- Summary of six key points from this section (3)
- Practical results
- Summary: practical example
- Thank you
Topics Covered
- Why prepare data?
- Six foundations for data preparation and modeling
- Applicability of general data preparation techniques
- What is data preparation?
- Ideal data
- Selecting data for modeling
- Tools
- Techniques
- Introducing information transmission
- Where to represent complexity?
- Information transmission by mode
- Signal and noise
- Practical results
Talk Citation
Pyle, D. (2008, December 3). Data preparation [Video file]. In The Business & Management Collection, Henry Stewart Talks. Retrieved November 12, 2024, from https://doi.org/10.69645/BICA4600.Export Citation (RIS)