From the course: Deep Learning and Generative AI: Data Prep, Analysis, and Visualization with Python
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Role of data in the machine learning workflow
From the course: Deep Learning and Generative AI: Data Prep, Analysis, and Visualization with Python
Role of data in the machine learning workflow
- [Narrator] In a previous lesson, we mentioned that by the end of data pre-processing, data is the foundation of solving machine learning problems. The data phase process begins with data collection where we gather relevant data from various sources. We then need to prepare the data. This means that data is cleaned pre-processed and transformed to make it suitable for analysis. Again, this involves handling missing values, outliers, inconsistencies, and feature engineering data is the learning material needed by machine learning models, and the data provides the models the necessary information for them to learn patterns and relationships. These insights enable the models to make predictions, classifications, or groupings to assess a model's performance, it is evaluated on a separate data set. The results of this evaluation offer important insights for determining the next steps in the machine learning process. Data acts as the driver of model improvement. Based on model performance,…
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