Kernel Methods Courses and Certifications

Stanford CS229 - Machine Learning - Summer 2019 - Kernel Methods & Support Vector Machine

Explore kernel methods and Support Vector Machines in machine learning, focusing on advanced techniques for data classification and pattern recognition in complex datasets.

• YouTube
• 1 hour 55 minutes
• On-Demand
• Free Video

Alan Turing Institute

The Mother of All Representer Theorems for Inverse Problems and Machine Learning - Michael Unser

Explore the mathematical foundations of inverse problems and machine learning, focusing on representer theorems, Banach spaces, and kernel methods for advanced data science applications.

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

MITCBMM

Fit Without Fear - An Over-Fitting Perspective on Modern Deep and Shallow Learning

Explore over-fitting in modern machine learning, challenging conventional wisdom and presenting kernel methods as a competitive alternative to deep learning. Insights on interpolation, generalization, and stochastic gradient descent.

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

HUJI Machine Learning Club

Gauss-Legendre Features for Scalable Gaussian Process Regression

Discover how Gauss-Legendre features enable efficient scaling of Gaussian process regression through low-rank kernel matrix approximation, offering faster computation for large datasets with poly-logarithmic feature requirements.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Video

Institute for Pure & Applied Mathematics (IPAM)

Some Novel Kernel-Based Divergences Between Probability Distributions

Explore novel kernel-based divergences between probability distributions, focusing on the Kullback-Leibler divergence with kernel covariance operators (KKL) and its regularized variant for distributions with disjoint supports.

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

Conference GSI

Information Theory with Kernel Methods

Explore entropy estimation in data science using kernel methods and quantum information theory for covariance matrices.

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

Harvard CMSA

Implicit Regularization via Uniform Convergence in Linear Models and Kernel Methods

Explore the statistical analysis of mirror descent algorithms and their convergence properties in machine learning, focusing on early-stopped methods and uniform learning theory applications.

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

Cracking Classification

Master essential classification algorithms including logistic regression, decision trees, KNN, Naive Bayes, and SVM. Learn to evaluate model performance and apply techniques to real-world datasets.

• CodeSignal
• On-Demand
• Free Certificate

Deep Learning Essentials

Explore neural networks, perceptrons, and deep learning fundamentals. Master backpropagation, stochastic gradient descent, and kernel methods through Python coding assignments.

• Coursera
• 15 hours 41 minutes
• On-Demand
• Free Online Course (Audit)

Statistical Learning

Explore cutting-edge statistical analysis techniques, from regression to advanced methods like kernel smoothing and support vector machines. Enhance data interpretation skills with hands-on Python examples.

• Coursera
• 4 days 18 hours 15 minutes
• On-Demand
• Free Online Course (Audit)

Simons Institute

Kernel Methods for Causal Inference

Explore kernel ridge regression for causal inference, covering dose responses, treatment effects, and extensions to various settings. Learn about consistency, efficiency, and robustness in estimation.

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

Is Linux Kernel Development Suitable for Safety-Critical Systems? - Progress and Methods

Explore Linux kernel development for safety-critical systems, examining methods to assess and improve its suitability for use in autonomous driving and other high-stakes applications.

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

Institute for Pure & Applied Mathematics (IPAM)

Exponential Concentration in Quantum Generative Modeling and Quantum Kernel Methods

Explore exponential concentration in quantum generative modeling and kernel methods, examining causes, consequences, and the impact of shot noise on these quantum machine learning models.

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

Linux Plumbers Conference

Formal Methods for Kernel Hackers

Discover how formal methods can benefit kernel development, find bugs, and improve design choices in Linux, with practical examples using PlusCal and TLA+.

• YouTube
• 44 minutes
• On-Demand
• Conference Talk

University of Tübingen

Statistical Machine Learning

2 reviews

Comprehensive exploration of machine learning concepts, from basic algorithms to advanced topics like kernels, dimensionality reduction, and clustering, with insights on societal impact and practical applications.

• YouTube
• 1 day 9 hours
• On-Demand
• Free Online Course