Regularization Courses and Certifications

Coursera

Deep Learning Model Engineering and Optimization

Master deep learning model engineering by selecting architectures, building PyTorch baselines, and optimizing models with regularization, hyperparameter tuning, and advanced techniques for production-ready performance.

• Coursera
• 5 weeks, 3 hours a week
• Self-Paced
• Paid Course

Machine Learning Course

Comprehensive exploration of machine learning fundamentals, covering linear models, neural networks, SVMs, and key principles for effective algorithm implementation and evaluation.

• YouTube
• 1 day
• Self-Paced
• Free Video

Data and Visual Analytics

This course will introduce students to the field by covering state­-of-­the-art modeling, analysis and visualization techniques.

• Udacity
• 2 hours
• Self-Paced
• Free Online Course

Regularization of Big Neural Networks

Explore regularization techniques for large neural networks, including DropOut, DropConnect, and stochastic pooling. Learn about deconvolutional networks and their applications in computer vision tasks.

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

Simons Institute

Deep Robust Reinforcement Learning and Regularization

Explore robust reinforcement learning, addressing uncertainties in deep RL through regularization techniques. Gain insights into robust MDPs, policy evaluation, and uncertainty-aware Bellman equations.

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

Simons Institute

Implicit Regularization I

Explore implicit regularization in deep learning, covering boosting, complexity control, optimization landscapes, and stochastic gradient descent for effective model training.

• YouTube
• 1 hour 17 minutes
• Self-Paced
• Free Video

Simons Institute

Implicit Regularization II

Explore implicit regularization in deep learning, focusing on advanced concepts and their impact on model performance and generalization.

• YouTube
• 1 hour 23 minutes
• Self-Paced
• Free Video

Simons Institute

Why Deep Learning Works: Implicit Self-Regularization in Deep Neural Networks

Explore the underlying mechanisms of deep learning's success, focusing on implicit self-regularization in neural networks and its impact on model performance.

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

Alan Turing Institute

Regularization for Optimal Transport and Dynamic Time Warping Distances - Marco Cuturi

Explore regularization techniques for optimal transport and dynamic time warping distances, focusing on smoothing strategies to enhance machine learning applications and Fréchet mean computation.

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

MITCBMM

Towards Understanding the Implicit Regularization Effect of SGD

Explore the implicit regularization effect of Stochastic Gradient Descent, uncovering its impact on optimization and generalization in machine learning models.

• YouTube
• 1 hour 14 minutes
• Self-Paced
• Free Video

Deep Learning Crash Course for Beginners

2 ratings

Comprehensive introduction to deep learning fundamentals, covering neural networks, learning types, architectures, and model development steps. No coding required, ideal for beginners.

• freeCodeCamp
• 1-2 hours
• Self-Paced
• Free Video

Society for Industrial and Applied Mathematics

Model Invariants and Functional Regularization

Explore model invariants and functional regularization in quantitative finance. Learn about regression, MLE, Bayesian estimation, and new approaches to improve model robustness and interpretability in data analysis.

• YouTube
• 50 minutes
• Self-Paced
• Conference Talk

International Mathematical Union

Modern Regularization Methods in Inverse Problems and Data Science

Explores recent developments in variational methods for inverse problems and machine learning, discussing convergent regularization schemes, quantitative estimates, and connections between classical regularization theory and risk minimization.

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

Fields Institute

Learning Linear Dynamical Systems with Hankel Nuclear Norm Regularization

Explore finite-sample analysis and insights for learning low-order linear dynamical systems using Hankel nuclear norm regularization, with applications in control and reinforcement learning.

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

International Centre for Theoretical Sciences

Regularization by Noise - Lecture 5

Dive into regularization by noise in fluid dynamics, exploring advanced mathematical concepts and their applications to Euler and Navier-Stokes equations in this comprehensive lecture.

• YouTube
• 1 hour 13 minutes
• Self-Paced
• Free Video