Inductive Bias Courses and Certifications

Yannic Kilcher

Discovering Symbolic Models from Deep Learning with Inductive Biases

Exploring how Graph Neural Networks and symbolic regression can derive accurate symbolic equations from observational data, combining deep learning with physics-inspired inductive biases.

• YouTube
• 46 minutes
• On-Demand
• Free Online Course

MIT EI Seminar - Phillip Isola - Emergent Intelligence- Getting More Out of Agents Than You Bake In

Explore emergent intelligence in AI through unsupervised learning, generative modeling, and self-assembling agents. Discover surprising outcomes beyond explicit programming in representation, video generation, and creature development.

• YouTube
• 58 minutes
• On-Demand
• Free Online Course

Machine Learning

Learn about machine learning, the area of artificial intelligence (AI) that is concerned with computational artifacts that modify and improve performance through experience.

• edX
• 14 weeks, 8-10 hours a week
• On-Demand
• Free Online Course (Audit)

Yannic Kilcher

An Image is Worth 16x16 Words - Transformers for Image Recognition at Scale

Explore how Transformers outperform CNNs in image recognition, delving into Vision Transformer architecture, experimental results, and implications for AI research.

• YouTube
• 30 minutes
• On-Demand
• Free Online Course

Yannic Kilcher

Noether Networks - Meta-Learning Useful Conserved Quantities

Explore Noether Networks: a novel approach to meta-learning conserved quantities in sequential prediction problems, inspired by Noether's theorem and aimed at discovering useful symmetries and inductive biases.

• YouTube
• 1 hour 9 minutes
• On-Demand
• Free Online Course

HuggingFace

The Future of Natural Language Processing

Explore transfer learning in NLP, covering model efficiency, generalization, fine-tuning, and inductive biases. Gain insights into current trends and future directions from HuggingFace's science lead.

• YouTube
• 1 hour 3 minutes
• On-Demand
• Free Online Course

MITCBMM

Beyond Empirical Risk Minimization - The Lessons of Deep Learning

Explore deep learning's challenge to traditional machine learning wisdom, examining the "double descent" risk curve and how over-parametrized models can generalize well despite perfect training fit.

• YouTube
• 47 minutes
• On-Demand
• Free Online Course

Simons Institute

Improved Machine Learning Algorithm for Predicting Ground State Properties

Efficient ML algorithm predicts ground state properties of quantum systems using geometric locality, requiring minimal data and scaling favorably for large systems.

• YouTube
• 1 hour 15 minutes
• On-Demand
• Free Online Course

Simons Institute

A Theory for Emergence of Complex Skills in Language Models

Explores statistical framework linking LLM cross-entropy loss to language skill competence, analyzing scaling laws' implications for efficient learning and emergence of complex abilities.

• YouTube
• 1 hour 5 minutes
• On-Demand
• Free Online Course

Simons Institute

Understanding the Robustness of Deep Learning

Exploring deep learning robustness, transfer learning dynamics, and overparameterization to gain insights into network functioning and improve model reliability under distribution shifts.

• YouTube
• 1 hour
• On-Demand
• Free Online Course

Yannic Kilcher

Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations

Explores challenges in unsupervised learning of disentangled representations, questioning assumptions and efficacy of current approaches through theoretical analysis and extensive experiments.

• YouTube
• 28 minutes
• On-Demand
• Free Online Course

Simons Institute

Large ML Potentials for Chemistry - Generalization, Inductive Biases, and Error Cancellation

Explore machine learning potentials in chemistry, focusing on generalization, inductive biases, and error cancellation techniques for improved accuracy and efficiency.

• YouTube
• 1 hour 1 minute
• On-Demand
• Free Online Course

FA17: Machine Learning

Learn about machine learning, the area of artificial intelligence (AI) that is concerned with computational artifacts that modify and improve performance through experience.

• edX
• 14 weeks, 8-10 hours a week
• Finished
• Free Online Course (Audit)