AI Project Cycle Class 9 Notes

A step-by-step process companies use to solve problems using AI. It helps ensure value from AI projects.

The initial stage of an AI project, where you define the problem by understanding its scope and impact.

Questions used in problem scoping to understand the problem's context: Who, What, Where, Why.

A concise summary of the problem, outlining its scope, stakeholders, and goals.

The process of gathering accurate and reliable data for an AI project.

A representation of facts or instructions in any form that can be processed or conveyed by humans or machines.

The collection of all the factors that directly or indirectly affect the problem in an AI project.

The method used to collect and prepare data for AI projects, ensuring it's suitable for analysis and training.

The process of determining how well an AI model performs after it's been trained.

A decision-making tool that uses a tree-like structure to make predictions based on data.

The process of choosing the simplest and most effective decision tree from multiple possible options.

Factors that directly influence the output of a decision tree.

Data that is organized in a standardized format, following a consistent structure and order. It can be easily accessed and understood by computer programs and humans.

Data that doesn't follow a predefined structure, making it difficult to store and manage. It's often found in the form of images, videos, audio files, and text documents.

A collection of data arranged in a table-like format, containing related numbers or values about a specific topic. For example, students' grades in a class.

A large portion of a dataset used to train a machine learning model. The model learns from this data to make predictions or perform tasks.

A smaller portion of a dataset used to evaluate the performance of a trained machine learning model. It helps determine how well the model generalizes to new data.

A type of data collection method that involves asking a group of people questions to gather insights or information. Surveys can be structured with multiple-choice answers or open-ended questions.

A process of collecting structured data from the internet. It involves using scripts to extract information from websites, often used for tasks such as market research and news monitoring.

A method of data collection based on carefully observing and noting information from the real world, often used in research studies.

A device that senses or measures a physical property, such as temperature, pressure, or movement. Data collected by sensors can be used to monitor systems and gather insights.

A software interface that allows different applications to communicate and exchange data with each other. It acts as a messenger between programs.

A visual representation of a system, showing its components and how they interact with each other. Arrows are used to depict the cause-and-effect relationships between elements.

Using statistical tools and visualizations to understand the characteristics of a dataset, such as its size, distribution, and accuracy. It's a way to gain insights into the data before analyzing it.

Visual representations of data that help make complex information easier to understand. They communicate a story using charts, graphs, and symbols.

The simulation of human intelligence in machines that have been trained to think and act like humans. It encompasses a wide range of tasks, from natural language processing to image recognition.

A subfield of artificial intelligence that focuses on training machines to learn from data without explicit programming. Machines learn by identifying patterns and relationships in datasets.

A type of machine learning that uses deep neural networks with multiple layers to analyze data, extract features, and make predictions. It's capable of learning complex patterns and relationships.

An AI modeling technique where the developer explicitly defines the rules and relationships between data elements. The machine follows these instructions to complete its tasks.

The process of creating AI models, which are programs trained to recognize patterns using data. It involves designing and building algorithms that can learn and make decisions.

An AI modeling technique where the developer doesn't specify the relationships between data elements. Instead, the machine learns patterns and trends from random data.