Global Certificate Course in Machine Learning Model Validation
-- viewing nowThe Global Certificate Course in Machine Learning Model Validation is a comprehensive program designed to equip learners with essential skills in machine learning model validation. This course is crucial in today's data-driven world, where businesses increasingly rely on machine learning models to make informed decisions.
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Course details
• Introduction to Machine Learning Model Validation
• Types of Machine Learning Model Validation
– K-fold Cross-validation
– Stratified K-fold Cross-validation
– Leave-One-Out Cross-Validation
– Holdout Validation
– Time Series Cross-Validation
• Performance Metrics for Model Validation
– Confusion Matrix
– Classification Metrics
– Regression Metrics
• Bias-Variance Tradeoff
• Overfitting and Underfitting in Machine Learning
• Techniques to Address Overfitting and Underfitting
– Regularization (L1 and L2)
– Ensemble Methods (Bagging, Boosting, and Stacking)
• Model Selection and Hyperparameter Tuning
– Grid Search and Random Search
– Bayesian Optimization
• Data Leakage and Its Prevention in Model Validation
• Introduction to Resampling Techniques
– Bootstrapping
– Cross-Validation and Bootstrapping Comparison
Career path
Entry requirements
- Basic understanding of the subject matter
- Proficiency in English language
- Computer and internet access
- Basic computer skills
- Dedication to complete the course
No prior formal qualifications required. Course designed for accessibility.
Course status
This course provides practical knowledge and skills for professional development. It is:
- Not accredited by a recognized body
- Not regulated by an authorized institution
- Complementary to formal qualifications
You'll receive a certificate of completion upon successfully finishing the course.
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