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Reinforcement Learning

Class 2. Bellman equations

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Reinforcement Learning - Previous Class 1. Introduction to intertemporal optimization Next - Reinforcement Learning Class 3. Hamiltonian analysis

Class 4. Ensemble
Class 4. Boltzmann machine
Regression Analysis II
Yeonsook Kwak (MBA, 2024)
Class 8. Summary of Math & Stat for MBA I
Class 4. Basic time series regression analysis
Game Theory
Class 6. Policy-based optimization
Probabilistic Graphical Models
Class 7. Summary of Math & Stat for MBA I
Advanced Deep Learning
Reinforcement Learning
Class 5. Probability models
Class 1. Introduction to intertemporal optimization
Class 2. Consumer choices
Class 6. Bayesian statistics
Class 7. Summary of Math & Stat for MBA II
SIAI Lecture Notes
Class 5. Image recognition
Math & Stat for MBA II
Law and AI
Class 8. Summary of Math & Stat for MBA II
Class 7. Deep Generative Models
Bayesian Statistics II
Class 2. Classification
Data-based Decision Making
Class 8. Summary of Deep Learning
Jeonghun Song (MSc, 2023)
Mincheol Kim (MSc, 2023)
Hyeyoung Park (MBA, 2023)
Class 4. ANOVA to Multivariate regression
Class 7. Large Language Model (LLM)
Class 5. Simulations
Class 3. Fourier transform
Sungsu Han (MBA, 2024)
Class 8. Summary of Machine Learning
Advanced Reinforcement Learning
AI in Corporate Finance
Class 6. Endogeneity – Measurement error
SIAI Yearbook
Class 5. Simulation and Bayesian
Class 8. Summary of Data-based Decision Making 2
Regression Analysis III
Social Network Analysis
Games with Incomplete Information
AI Business Cases
Class 3. Causality in data science
Class 8. Summary of Scientific Programming
Class 7. Optimization methods
Panel Data Analysis
Bayesian Statistics I
Class 5. Endogeneity – Correlation between errors and regressors
Class 2. Autoencoder
AI in Asset Management
Information Theory
Donggyu Kim (MBA, 2024)
Jeongwoo Park (MSc, 2023)
Bohyun Yoo (MBA, 2023)
Class 1. Basic statistics
Class 1. Comparative advantage
Hyoung Keun Kwon (MSc, 2024)
Class 4. Finite differences
Scientific Programming
Class 6. Variance reduction
Class 2. Generalized least square
Deep Learning
Class 3. Data grouping
Class 6. Endogeneity 2 – Correlation between errors and regression
Class 8. Summary of Reinforcement Learning
Class 2. Exact matching via quadrature
Class 5. Dimensionality reduction
Class 2. Basic statistics
Class 7. Artificial Neural Network
Class 4. Time series II – Seasonality and frequency
Class 3. Time Series – ACF and PACF
Class 1. Approximations and computational cost
Class 6. Factor analysis
Data Visualization
AI in Digital Marketing
Class 3. Hamiltonian analysis
Class 1. Regression problems
Books
Regression Analysis I
Data Management
Machine Learning
Class 3. Basic statistics
Class 4. First-order differential equations (FODE)
SIAI Yearbook – 2024
Math & Stat for MBA I
Class 5. Value-based optimization
Class 3. MCMC and Bayesian extensions
Class 1. Large sample properties and maximum likelihood
Class 6. Recurrent Neural Network
SIAI Yearbook – 2023
Class 7. Summary of Data-based Decision Making 1
Class 1. Introduction to deep learning
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Class 2. Bellman equations

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Global Institute of Artificial Intelligence(GIAI) LLC. is an academic association with a group of scientifically trained researchers in the field of AI/Data Science. The institution runs multiple business lines including AI/Data Science consultancy, academic journals, graduate school level higher education, and business journals dedicated to technological advance.

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