Business Intelligence and Analytics - Classification Models in Python - Tuning Hyperparameters
Master Data Mastery: Transform, Analyze, and Visualize! Dive into the world of Big Data, Governance, Python Analytics, Machine Learning, and AI with Stephanie Powers. Unlock data's power and elevate your expertise in modern analytics and data engineering. Enroll now!
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31 learners
What you'll learn
Understand and apply data governance principles to manage data effectively.
Analyze data types and structures using Python for data engineering tasks.
Create dashboards and visualizations in Python to present analytical insights.
Implement machine learning models in Python for classification and prediction tasks.
This course includes
56.5 hours of video
Certificate of completion
Access on mobile and TV
Summary
Full Transcript
This video shows how to tune hyperparameters in Python to improve the accuracy of Decision Trees, Random Forest, and Gradient Boosting Machine classification models. It also includes K-Fold and Stratified K-Fold cross validation to assess the tuned model.
Python workbook available here: https://drstephpowers.github.io/BIA/
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