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

Python for Info Science — Half 14/30

Desk of Contents
1. Understanding ML Pipelines
2. Info Preprocessing in ML Pipelines
2.1. Exploratory Info Analysis (EDA)
2.2. Perform Engineering
3. Model Setting up and Teaching
3.1. Algorithm Alternative
3.2. Hyperparameter Tuning
4. Evaluation and Validation
4.1. Cross-Validation Strategies
4.2. Effectivity Metrics
5. Deployment in Python
5.1. Model Serialization
5.2. Web Deployment with Flask
6. Conclusion and Further Learning

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1. Understanding ML Pipelines

Machine Learning (ML) pipelines are systematic workflows that automate the tactic of establishing and deploying ML fashions ML pipelines. They streamline all of the course of, from info…