Hyperparameter Tuning in Python: Boost Model Accuracy with Scikit-Learn
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In this step-by-step tutorial, you'll learn how to fine-tune hyperparameters in your machine learning models using RandomizedSearchCV in Python’s most popular ML library — Scikit-Learn.
Whether you're working with Random Forests, SVMs, or Gradient Boosting, mastering hyperparameter tuning is the key to improving model performance and achieving higher accuracy.
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🎬 Timestamps:
00:00 | Hyperparameter Tuning in ML
2:00 | Machine Learning Pipeline
6:40 | GridSearchCV vs RandomizedSearchCV
9:25 | Scikit-Learn Docs
14:35 | How to use RandomizedSearchCV
18:15 | Matplotlib in Machine Learning
22:00 | Refactor the Pipeline
28:30 | Our Results
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