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Related lectures (50)
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Chemical Environments: Representations and Correlations
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Explores chemical environment representations, symmetrized correlations, and machine learning applications at the atomic scale.
Structural Mechanics Principles: Equilibrium and Stability
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Explores the principles of structural mechanics, including internal loads, equilibrium stability, and the superposition principle.
Introduction to Data Science
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Introduces the basics of data science, covering decision trees, machine learning advancements, and deep reinforcement learning.
Understanding Machine Learning: Exactly Solvable Models
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Explores the statistical mechanics of learning, focusing on neural networks' mysteries and computational challenges.
Introduction to Machine Learning
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Covers the basics of machine learning, including supervised and unsupervised learning, linear regression, and classification.
Protein Design: Structure and Function
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Covers protein design fundamentals, including secondary structures, amino acid propensity, loops, and computational methods.
Neural Networks Recap: Activation Functions
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Covers the basics of neural networks, activation functions, training, image processing, CNNs, regularization, and dimensionality reduction methods.
Deep Learning: Multilayer Perceptron and Training
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Covers deep learning fundamentals, focusing on multilayer perceptrons and their training processes.
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Block Pulled by a Spring
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Explores the dynamics of a block pulled by a spring under various conditions.
Boltzmann Equation: Scattering Term
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Covers the Boltzmann equation's scattering term and carrier scattering, including phonons, electrons, photons, and molecules.
Thermo-Calc: Exercise and Property Models
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Explores Thermo-Calc software for defining functions and property models in materials science.
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Phase Transitions in Physics and Machine Learning
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Explores phase transitions in physics and computational problems, highlighting challenges faced by algorithms and the application of physics principles in understanding neural networks.
Plane Trusses: Analysis and Strategies
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Covers the analysis of rigid structures and strategies to solve isostatic trusses.
Protein Structure Prediction
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Delves into predicting protein structure through amino acid contact analysis and advanced computational methods.
Neural Taskonomy and Historical Perspectives in Visual Intelligence
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Covers Neural Taskonomy, the evolution of neural networks, and historical perspectives in visual intelligence.
Introduction to Structural Mechanics
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Introduces resultants in 3D, equilibrium in 2D, and free-body diagrams for structural analysis.
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