CBSE 9 AI (Artificial Intelligence) | 19. INPUT by Abraham | Learn Smarter
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19. INPUT

19. INPUT

The chapter examines the critical role of input data in Artificial Intelligence systems, emphasizing how various data types are essential for effective learning and decision-making processes. It discusses the significance of quality input for accurate predictions, explores notable data collection methods, and highlights ethical considerations surrounding data use. Through various applications, the chapter underscores the importance of input in powering real-life AI functionalities ranging from virtual assistants to self-driving cars.

17 sections

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Sections

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  1. 19

    The input stage in AI encompasses the collection and preparation of data...

  2. 19.1
    What Is Input In Ai?

    Input in AI refers to the data fed into an AI system for processing and...

  3. 19.2
    Importance Of Input

    Input data is crucial for the effectiveness and accuracy of AI systems,...

  4. 19.3
    Types Of Input Data

    This section introduces the various types of input data utilized in AI,...

  5. 19.3.1
    Structured Data

    Structured data is organized in a predictable format, making it easier for...

  6. 19.3.2
    Unstructured Data

    Unstructured data lacks a specific format, making it complex to analyze but...

  7. 19.3.3
    Semi-Structured Data

    Semi-structured data is a type of data that is partially organized but does...

  8. 19.4
    Sources Of Input Data

    This section discusses the different sources from which input data for AI...

  9. 19.5
    Data Collection Methods

    This section discusses different data collection methods used in AI,...

  10. 19.5.a
    Manual Data Entry

    Manual data entry involves human input of data, which, while time-consuming,...

  11. 19.5.b
    Web Scraping

    Web scraping is an automated method for extracting data from websites,...

  12. 19.5.c
    Apis (Application Programming Interfaces)

    APIs are essential tools that enable systems to access and share data...

  13. 19.5.d
    Sensors And Devices

    This section explains how sensors and devices are critical for gathering...

  14. 19.6
    Data Validation And Cleaning

    This section discusses the importance of validating and cleaning data before...

  15. 19.7
    Tools Used For Input Processing

    This section outlines the various tools and technologies used for processing...

  16. 19.8
    Real-Life Applications Of Input In Ai

    This section discusses real-world examples of how input data is utilized in...

  17. 19.9
    Ethical Considerations In Input Collection

    This section discusses the ethical considerations surrounding the collection...

What we have learnt

  • Input is crucial for AI systems, serving as the foundational data for processing.
  • Input data can be structured, unstructured, or semi-structured, each with its own uses and challenges.
  • Proper methods of data collection, validation, and cleaning significantly impact the effectiveness of AI systems.
  • Ethical considerations, including privacy, consent, and security, are essential in the collection and use of input data.

Key Concepts

-- Input Data
Data or information fed into an AI system for processing, learning, and decision-making.
-- Structured Data
Organized information formatted in rows and columns, such as databases, making it easy to analyze.
-- Unstructured Data
Data without a predefined format, including images, audio, and social media posts, requiring special tools for analysis.
-- Data Collection Methods
Various techniques used to gather data, including manual entry, web scraping, APIs, and sensors.
-- Data Cleaning
The process of correcting or removing erroneous data to improve the quality before analysis.
-- Ethical Considerations
Principles guiding the responsible collection and usage of data, focusing on privacy, consent, bias, and security.

Additional Learning Materials

Supplementary resources to enhance your learning experience.