Learn how to implement data transformation in an end-to-end machine learning project using pipelines. Explore techniques for handling categorical values, missing data, and standard scaling. Follow along as the instructor demonstrates importing necessary libraries, configuring data transformation, creating a data transformer using pipelines, initiating the transformation process, and testing the results. Gain practical insights into saving the pickle file in the artifact folder and integrating data transformation with data ingestion in a real-world ML project.
Overview
Syllabus
Agenda
Import necessary libraries
Data Transformation Config
Create Data Transformer using Pipeline
Initiate Data Transformation
Test Data Transformation and Ingestion
Taught by
Krish Naik
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