Questions and Answers
Which of these options are considered types of data in AI?
Continuous data can include whole numbers.
False
What is data acquisition?
The procedure of gathering data.
What is one example of numeric data?
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Match the following types of data with their respective domains in AI:
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Data is the fuel that powers _______.
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Name a limitation that might be mentioned regarding data usage?
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Which dataset might you find on Kaggle?
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Study Notes
Learning Outcomes
- Familiarity with data terminologies: acquisition, processing, analysis, presentation, and interpretation.
- Understanding methods of data interpretation: qualitative vs quantitative.
- Knowledge of various data collection techniques and their advantages and disadvantages.
- Ability to identify diverse data presentation methods with examples for interpretation.
- Awareness of the significance and impact of data interpretation on business growth.
Activity: Top-Secret Weather Mission
- Objective: Train an AI model for weather prediction using acquired datasets.
- Teamwork: Form pairs to collaboratively locate weather forecast datasets online.
- Suggested intel sources:
- Kaggle: Access a variety of datasets; search for "weather forecast dataset."
- Quandl: A repository for financial/economic data; includes potential weather data.
- Open Weather Map: Explore for historical weather data insights.
- Mission Steps:
- Infiltrate websites for weather datasets.
- Capture relevant datasets with screenshots or images.
- Discuss findings with partners regarding the most relevant datasets and their contents (e.g., temperature, precipitation).
Types of Data in AI
-
Textual Data (Qualitative):
- Composed of words and phrases, used in Natural Language Processing (NLP).
- Examples include search queries.
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Numeric Data (Quantitative):
- Composed of numbers, essential for statistical analysis and modeling.
- Examples include cricket scores and restaurant bills.
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Further Classification of Numeric Data:
- Continuous Data: Has a continuous range of values (e.g., height, weight, temperature).
- Discrete Data: Consists of whole numbers (e.g., number of students in a class).
Domains of AI Data Types
-
Computer Vision (CV):
- Deals with visual data such as images and videos.
-
Natural Language Processing (NLP):
- Involves textual data, including documents and PDF files.
-
Statistical Data (SD):
- Consists of numeric data presented in tables or Excel sheets.
Data Acquisition
- Refers to the process of gathering data essential for training AI models.
- Steps in data acquisition typically include:
- Identifying appropriate datasets.
- Searching for suitable sources.
- Collecting the data for processing and analysis.
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Description
Test your knowledge on data literacy concepts, including data acquisition, processing, and interpretation. This quiz covers various data collection techniques and encourages critical thinking about qualitative and quantitative data methods. Familiarize yourself with essential terminologies and their applications.
