Question
Which of the following techniques is most suitable for
handling and organizing an unstructured dataset with textual data?Solution
Text parsing and tokenization are crucial steps for processing unstructured textual data. Parsing involves extracting and structuring data from text, while tokenization breaks down text into meaningful elements or "tokens" for analysis. This approach is particularly useful for unstructured datasets like customer reviews, social media comments, or any free-form text where content analysis is required. By structuring the data through tokenization, a data analyst can perform further analysis, like sentiment analysis or topic modeling, to extract insights from textual data. The other options are incorrect because: • Linear Regression is a statistical technique, unsuitable for unstructured text. • Data Normalization standardizes numeric values, not text. • Data Aggregation consolidates data, but doesn't handle text processing specifically. • K-means Clustering groups data, but tokenization is first needed for textual data.
In which type of farming do farmers grow crops mainly to feed their families?
A boat will submerge when it displaces water equal to its own:
India’s first greenfield grain based ethanol production plant inaugurated in ………………….
Heat energy transmitted through collisions between neighboring atoms or molecules is called ________.
The yearly sequence and spatial arrangement of crops or of crops and fallow on a given area is known as
…………………………State Government has launched the trees outside forest in India programme in association with USAID.
...The scientific study of diseases in plants, identification of the pathogen and their management is known asÂ
Who has been designated as the "Youth Voter Awareness Ambassador" for Jammu & Kashmir by the Election Commission of India?
The theme for the Word food Day, which was observed on 16th October 2022 was:
The world’s largest coral reef isÂ