Conformal Bootstrap: Recap and Primary Concepts

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Covers CNNs, RNNs, SVMs, and supervised learning methods, emphasizing the importance of tuning regularization and making informed decisions in machine learning.

Unsupervised Learning: Clustering

Explores unsupervised learning through clustering techniques, algorithms, applications, and challenges in various fields.

Local Fields and Correlations in Ising Models

Covers local fields and correlations in Ising models and conformal field theory.

Introduction to Image Classification

Covers image classification, clustering, and machine learning techniques like dimensionality reduction and reinforcement learning.

Conformal Field Theory: Generators and Commutation Relations

Covers the definition of generators of the conformal group and the application of Wick's theorem.

Conformal Blocks: Understanding Young Diagrams and Weight States

Covers conformal blocks, Young diagrams, and their significance in weight states.

FK-Percolation and the Six-Vertex Model: Critical Phenomena

Covers the transition from the six-vertex model to FK-percolation, focusing on critical phenomena and phase transitions in two-dimensional systems.

Conformal Loop Ensembles: Connections to CFT

Explores the relationship between conformal loop ensembles and conformal field theory, focusing on the three-point nesting function and its mathematical derivation.

Conformal Transformations and Stress Tensor

Explores conformal transformations, stress tensor, and correlation functions in conformal field theory.