Machine Learning
Building Reusable Pipeline Functions
This course lays the groundwork for a robust MLOps pipeline by developing core functions that will be reused in subsequent courses. Rather than focusing on the full data science process, learners will implement specific, modular components for data processing, model training, evaluation, and persistence—all critical for later integration in automated retraining and API-based serving.
Pandas
Python
Scikit-learn
4 lessons
21 practices
3 hours
Badge for Machine Learning Model Development,
Machine Learning Model Development
Course details
Building Reusable Data Processing Functions
Fix the Data Processing Bug
Loading Diamonds Dataset Correctly
Identifying Data Columns Efficiently
Building a Robust Preprocessing Pipeline
Building a Data Processing Module
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