Regularization Courses and Certifications

Machine Learning: Regression

This course covers key supervised machine learning topics in regression analysis. You’ll learn to train and test regression models. Ideal for aspiring data scientists and machine learning engineers.

• edX
• 2 weeks, 20-24 hours a week
• On-Demand
• Free Online Course (Audit)

Coursera

Start Neural Networks Advanced Model Architectures

Master advanced neural network architectures with hands-on Keras/PyTorch implementation, regularization techniques, and systematic evaluation for real-world applications.

• Coursera
• 2 hours 16 minutes
• On-Demand
• Paid Course

Coursera

Optimize Deep Learning: Stabilize and Diagnose Models

Master deep learning optimization by stabilizing and diagnosing models, exploring techniques to improve performance, identify issues, and build resilient neural networks for real-world applications.

• Coursera
• 1 hour 57 minutes
• On-Demand
• 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
• On-Demand
• Free Video

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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• 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
• On-Demand
• Free Video

Machine Learning and AI Foundations: Recommendations

325 ratings at LinkedIn Learning

This project-based course shows programmers of all skill levels how to use machine learning to build programs that can make recommendations—like recommending new products.

• LinkedIn Learning
• 58 minutes
• On-Demand
• Free Trial Available

Deep Learning: Model Optimization and Tuning

208 ratings at LinkedIn Learning

Learn about various optimization and tuning options available for deep learning models and use them to improve models.

• LinkedIn Learning
• 54 minutes
• On-Demand
• Free Trial Available

Deep Learning Crash Course for Beginners

2 reviews

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
• On-Demand
• 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
• On-Demand
• Free Video