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Concept

Scale model

Related lectures (29)

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Explores training strategies for Transformers in NLP and Vision, emphasizing rapid advancements and challenges in scaling models.

Scaling Language Models

Explores the challenges and benefits of scaling language models, emphasizing the importance of scaling laws in estimating optimal model and dataset sizes.

Polymer Modeling: Interactions and Scaling Behavior

Explores polymer modeling, interactions, and scaling behavior of real polymers.

Model Selection Criteria: AIC, BIC, Cp

Explores model selection criteria like AIC, BIC, and Cp in statistics for data science.

Scaling Language Models: Efficiency and Deployment

Covers the scaling of language models, focusing on training efficiency and deployment considerations.

Turbulent Energy Dissipation

Explores turbulence models for energy dissipation and kinetic energy transport.

Red bus/Blue bus paradox

Explores the Red bus/Blue bus paradox, nested logit models, and multivariate extreme value models in transportation.

Incompressible Fluid Mechanics

Explores incompressible fluid mechanics, focusing on potential flows and flow patterns.

Currents in the O(n) Model: Conformal Field Theory Insights

Covers the O(n) model on the hexagonal lattice and its currents.

Percolation Theory

Covers percolation theory, absorbed polymers, giant molecules, phase transition, scaling assumptions, and universal behavior in percolation models.

IAQ and Ventilation: Mass-Balance Principles

Explores mass-balance principles and air-exchange rates for indoor air quality assessment.

Random Field Ising Model

Covers the Random Field Ising Model, discussing the concept of disorder and the process of finding the ground state.

Maximum Likelihood Inference

Explores maximum likelihood inference, comparing models based on likelihood ratios and demonstrating with a coin example.

Modern NLP: From GPT to ChatGPT

Explores the evolution of modern NLP from GPT-2 to GPT-3, emphasizing in-context learning and the development of ChatGPT.

B-physics anomalies: data, EFT analyses, and model-building

Explores B-physics anomalies, EFT analyses, and model-building considerations in the context of Lepton Flavor Universality violations and semi-leptonic decays of the b quark.

Optimal Control: Convergence and Conditions

Covers the convergence and conditions for optimal control.

Machine Learning Biases

Covers the basics of machine learning, challenges in deployment, adversarial attacks, and privacy concerns.

Car following models: Intro to traffic flow modeling MOOC: Intro to Traffic Flow Modeling and Intelligent Transport Systems

Covers car following models, stability, lane changing, and microsimulation advantages, challenges, and characteristics.

Diophantine Approximation on Manifolds: Lower Bounds

Covers Diophantine approximation on manifolds with a focus on lower bounds.

River Hydraulics and Modeling: Semi-Distributed Approach

Explores river hydraulics, modeling, and calibration using a semi-distributed approach for accurate forecasting and water resource management.