Regularization Courses and Certifications

Learn to improve machine learning model performance on new data using regularization techniques like ridge and lasso, minimizing overfitting and understanding the bias-variance tradeoff.

• Codecademy
• 2 hours
• Self-Paced
• Free Trial Available

Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization

63522 ratings at Coursera

Enhance deep learning skills: master hyperparameter tuning, regularization, optimization, and TensorFlow implementation for improved neural network performance and systematic results generation.

• Coursera
• 23 hours 35 minutes
• Self-Paced
• Paid Course

Simons Institute

Discrepancy Minimization via Regularization

Explore a novel algorithmic framework for discrepancy minimization, reinterpreting key breakthroughs and proving conjectures for pseudorandom instances through regularization techniques.

• YouTube
• 57 minutes
• Self-Paced
• Free Video

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
• Self-Paced
• Free Certificate

Mastering Neural Networks and Model Regularization

Dive deep into neural networks, from perceptrons to CNNs. Build models from scratch, master regularization techniques, and apply PyTorch for image and audio processing tasks.

• Coursera
• 16 hours 3 minutes
• Self-Paced
• Paid Course

Richard McElreath

Statistical Rethinking 2023 - Fitting Over & Under

Explore advanced statistical concepts including cross-validation, regularization, and robust regression to enhance model fitting and selection techniques in data analysis.

• YouTube
• 1 hour 5 minutes
• Self-Paced
• Free Video

DeepLearning.AI;  Stanford

Supervised Machine Learning: Regression and Classification

32311 ratings at Coursera

Develop machine learning skills using Python, covering regression and classification techniques with hands-on practice in NumPy and scikit-learn for real-world AI applications.

• Coursera
• 1 day 9 hours 19 minutes
• Self-Paced
• Paid Course

ICTP-SAIFR

Issues Related to Regularizing Thermo and Magnetic Contributions within Nonrenormalizable Theories

Explore regularization challenges in thermo and magnetic contributions for nonrenormalizable theories in strongly interacting matter.

• YouTube
• 35 minutes
• Self-Paced
• Free Video

Centre International de Rencontres Mathématiques

From Correlated to White Transport Noise in Fluid Models

Explore stochastic dynamics in incompressible fluids through variational frameworks, examining large-scale behavior with small-scale processes and noise regularization effects.

• YouTube
• 47 minutes
• Self-Paced
• Free Video

MITCBMM

The Learning Problem and Regularization

Explore the foundations of machine learning with Prof. Poggio, covering key concepts like generalization, consistency, and regularization in solving learning problems.

• YouTube
• 1 hour 19 minutes
• Self-Paced
• Free Video

Deep Learning with PyTorch

12 ratings at DataCamp

Learn to create deep learning models with the PyTorch library.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Data Science Courses

Deep Learning: Regularization and Neural Network Normalization Techniques - Lecture 7

Dive into advanced deep learning concepts including layer normalization, FRN, TLU, and Keras implementation while mastering essential regularization techniques and gradient management.

• YouTube
• 52 minutes
• Self-Paced
• Free Video

Data Science Courses

Deep Learning - Regularization Techniques - Lecture 4

Dive into advanced regularization techniques for deep learning, covering weight decay, early stopping, and noise injection methods to enhance model performance and prevent overfitting.

• YouTube
• 1 hour 18 minutes
• Self-Paced
• Free Video

Institut Henri Poincaré

Structured Regularization Summer School 2017

Dive into advanced mathematical techniques for structured regularization through expert lectures covering optimization, machine learning, and signal processing applications.

• YouTube
• 22 hours 32 minutes
• Self-Paced
• Free Video

Credential

Comprehensive Introduction to PyTorch

209 ratings at CodeSignal

Master PyTorch fundamentals through hands-on exercises, progressing from tensor basics to advanced neural networks and model optimization techniques using real-world datasets like wine classification.

• CodeSignal
• 11 hours
• Self-Paced
• Free Certificate
• 4 courses