Page 170 - Ai Book - 10

I In a n a NNutshellutshell

• The process of developing machines has different stages that are collectively known as ‘AI Project Cycle.’
• The steps involved in an AI project life cycle are: Problem scoping, Data Acquisition, Data Exploration,
Modelling and Evaluation.
• The first step of an AI project life cycle is defining the scope of a problem.

• Data Acquisition plays an important role because the whole project is carried out on the basis of identified
requirements.
• Data Exploration is the process of understanding the nature of data in terms of quality, characteristics etc.
that you have to work with.
• Modelling is the fourth stage in which collected data must be analysed according to the gathered project
requirements.

• The last step of the AI project life cycle is Deployment.
• Data feature refers to the type of data that you want to collect for the problem scoped.
• Rule-based systems are static whereas learning based systems are dynamic due to the adaptability of new
user inputs and information.

• An Artificial Neural Network can be defined as a computing system made up of simple, highly interconnected
processing elements which process information by their dynamic state response to external inputs.
Composed of artificial neurons. Input, hidden, and output layers process information.

• Neural networks are widely used for pattern recognition and classification tasks. It can adjust to new
environments without preset instructions

S Solvedolved QQuestionsuestions

A. Tick () the correct answer.

1. What is the first step in the AI Project Cycle?
a. Data Acquisition b. Problem Scoping

c. Data Exploration d. Modelling
2. What is the purpose of the 4W’s Problem Canvas?

a. Collecting data
b. Identifying stakeholders and the problem scope

c. Training the model
d. Data exploration
3. Which stage involves identifying and gathering the necessary data for an AI project?

a. Data Exploration b. Data Modelling
c. Data Acquisition d. Evaluation

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