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a) problem scoping

b) data acquisition

c) data exploration

d) modelling
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B) Data Acquisition


  • Data acquisition is the stage in the AI project cycle where data from multiple sources is collected, cleared and aggregated in a suitable format and normalized. 
  • This is an important step as the quality and quantity of data will greatly impact the performance and accuracy of the AI models developed in later stages of the project. 
  • Data can be collected from a variety of sources such as databases, sensors, and external sources such as social media or publicly available datasets. 
  • This data must be cleaned and preprocessed to ensure that it is in a format that can be used by the AI models in the next stages.

Study more about Data acquisition at Data Acquisition Class10 

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