AI Python 14 — Machine Learning Pipelines in Python: From Data to Deployment | by Ayşe Kübra Kuyucu | Nov, 2024

Python for Information Science — Half 14/30

Desk of Contents
1. Understanding ML Pipelines
2. Information Preprocessing in ML Pipelines
2.1. Exploratory Information Evaluation (EDA)
2.2. Function Engineering
3. Mannequin Constructing and Coaching
3.1. Algorithm Choice
3.2. Hyperparameter Tuning
4. Analysis and Validation
4.1. Cross-Validation Methods
4.2. Efficiency Metrics
5. Deployment in Python
5.1. Mannequin Serialization
5.2. Internet Deployment with Flask
6. Conclusion and Additional Studying

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1. Understanding ML Pipelines

Machine Studying (ML) pipelines are systematic workflows that automate the method of constructing and deploying ML fashions ML pipelines. They streamline all the course of, from information…