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Big Data vs. Data Science: Demystifying the Buzzwords

Pickl AI

This crucial step involves handling missing values, correcting errors (addressing Veracity issues from Big Data), transforming data into a usable format, and structuring it for analysis. This often takes up a significant chunk of a data scientist’s time. Think graphs, charts, and summary statistics.

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Large Language Models: A Complete Guide

Heartbeat

This step involves several tasks, including data cleaning, feature selection, feature engineering, and data normalization. It is therefore important to carefully plan and execute data preparation tasks to ensure the best possible performance of the machine learning model.