Overfitting Courses and Certifications

Donato Capitella

Evaluation Metrics, Overfitting and Underfitting in Machine Learning Models - Episode 3.5

Master essential model evaluation concepts and techniques, from accuracy metrics to handling overfitting through regularization and data augmentation, with practical MNIST model examples.

• YouTube
• 16 minutes
• On-Demand
• Free Video

UofU Data Science

Decision Trees and Overfitting in Machine Learning - Lecture 6

Dive into advanced concepts of decision trees, focusing on overfitting challenges and practical solutions for building more robust machine learning models.

• YouTube
• 47 minutes
• On-Demand
• Free Video

UofU Data Science

Decision Trees in Machine Learning: Practical Concerns and Overfitting - Lecture 5

Delve into practical aspects of decision tree learning, exploring implementation challenges and understanding how to address overfitting in machine learning models.

• YouTube
• 1 hour 19 minutes
• On-Demand
• Free Video

UofU Data Science

Decision Trees and Overfitting in Machine Learning - Lecture 5

Dive into practical aspects of decision tree learning, exploring overfitting challenges and essential implementation considerations in machine learning applications.

• YouTube
• 59 minutes
• On-Demand
• Free Video

Simons Institute

Generalization and Overfitting in Two-Layer Neural Networks

Delve into the theoretical understanding of generalization in overparametrized neural networks, exploring concepts like implicit bias, benign overfitting, and feature learning through statistical physics approaches.

• YouTube
• 59 minutes
• On-Demand
• Free Video

ACM SIGPLAN

Enhancing APR with PRISM - A Semantic-Based Approach to Overfitting Patch Detection

Discover PRISM, a semantic-based technique that detects overfitting patches in automatic program repair while preserving correct fixes and reducing developer review burden.

• YouTube
• 14 minutes
• On-Demand
• Free Video

Advanced Machine Learning Models for Prediction

3 reviews

Master advanced machine learning algorithms including SVM, decision trees, random forests, and neural networks for predictive modeling using Scikit-Learn, with focus on practical implementation and optimization.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Modeling the Iris Dataset with TensorFlow

Master TensorFlow fundamentals through hands-on practice with the Iris dataset, covering data preprocessing, model building, performance evaluation, early stopping implementation, and model deployment techniques.

• CodeSignal
• 3 hours
• On-Demand
• Free Certificate

Drawing Recognition with CNNs for Sketches

Master CNN architecture and training techniques to build effective hand-drawn sketch recognition systems with practical model evaluation and performance optimization methods.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

Fixing Classical Models – Diagnosis & Regularization

Discover how to diagnose and fix underperforming ML models through evaluation metrics, regularization techniques, capacity tuning, and early stopping with scikit-learn and XGBoost.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

Improving Neural Networks with PyTorch

Master advanced PyTorch techniques like dropout, early stopping, and batch normalization to transform weak neural networks into robust, high-performing models through hands-on implementation.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

Foundations of Gradient Boosting

Master gradient boosting by building decision trees, creating ensembles, and understanding feature importance through hands-on banking data analysis and model optimization.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

XGBoost for Beginners

Master XGBoost fundamentals to build faster, accurate models with parameter tuning, early stopping techniques, and native interface configuration for optimal performance.

• CodeSignal
• 1 hour
• On-Demand
• Free Certificate

fast.ai

Practical Deep Learning For Coders

7 reviews

Learn how to get a GPU server online suitable for deep learning— to creating state of the art, highly practical, models for computer vision, natural language processing, and recommendation systems.

• Independent
• 7 weeks, 10 hours a week
• On-Demand
• Free Online Course

Data Analytics Foundations for Accountancy II

11 ratings at Coursera

Explore machine learning concepts, algorithms, and practical applications in data analytics using Python. Gain skills in classification, regression, clustering, and anomaly detection for business insights.

• Coursera
• 2 days 22 hours 1 minute
• On-Demand
• Paid Course