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Improving Machine Learning and Deep Learning Models: Fixing Classical Models – Diagnosis & Regularization

In this course, learners will improve a poorly performing classical ML model using core diagnostic and regularization techniques. The model starts off weak, and learners fix it step by step through

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Last updated Tue, 07-Oct-2025
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Course overview

In this course, learners will improve a poorly performing classical ML model using core diagnostic and regularization techniques. The model starts off weak, and learners fix it step by step through evaluation, regularization, capacity tuning, and early stopping. All models are built using scikit-learn or XGBoost.

What will i learn?

  • Machine Learning and Predictive Modeling
  • Model Evaluation, Validation, and Selection
  • Deep Learning and Neural Networks
Requirements
Curriculum for this course
21 Lessons 44 mins
Improving Machine Learning and Deep Learning Models: Fixing Classical Models – Diagnosis & Regularization
1 Lessons 00:44:00 Hours
  • Improving Machine Learning and Deep Learning Models: Fixing Classical Models – Diagnosis & Regularization
    Preview 00:44:00
Evaluating Classification Models: Confusion Matrix and Classification Report
5 Lessons
  • Lesson: Evaluating Classification Models: Confusion Matrix and Classification Report
    Preview .
  • Practice: Fixing Models with One Parameter Change
    Preview .
  • Practice: Building a Confusion Matrix from Scratch
    Preview .
  • Practice: Calculating Classification Metrics by Hand
    Preview .
  • Practice: Fixing Misaligned Evaluation Metrics
    Preview .
Tuning L2 Regularization in Logistic Regression
5 Lessons
  • Lesson: Tuning L2 Regularization in Logistic Regression
    Preview .
  • Practice: Testing Regularization Strength in Action
    Preview .
  • Practice: Comparing L1 and L2 Regularization Effects
    Preview .
  • Practice: Refactoring Regularization for Better Reuse
    Preview .
  • Practice: Visualizing Regularization Effects with Matplotlib
    Preview .
Tuning Tree Depth to Prevent Overfitting in Decision Trees
5 Lessons
  • Lesson: Tuning Tree Depth to Prevent Overfitting in Decision Trees
    Preview .
  • Practice: Limiting Tree Depth to Prevent Overfitting
    Preview .
  • Practice: Tracking Tree Depth Performance Patterns
    Preview .
  • Practice: Fixing Swapped Metrics in Performance Reports
    Preview .
  • Practice: Automating Optimal Tree Depth Selection
    Preview .
Early Stopping with XGBoost: Preventing Overfitting in Boosted Trees
5 Lessons
  • Lesson: Early Stopping with XGBoost: Preventing Overfitting in Boosted Trees
    Preview .
  • Practice: Implementing Early Stopping in XGBoost
    Preview .
  • Practice: Fixing Early Stopping Validation Bug
    Preview .
  • Practice: Using the Best Iteration for Predictions
    Preview .
  • Practice: Finding the Best Early Stopping Setting
    Preview .
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About instructor
Includes:
  • 44 mins On demand videos
  • 21 Lessons
  • Access on mobile and tv
  • Full lifetime access