_toc.yml

# Table of contents
# Learn more at https://jupyterbook.org/customize/toc.html

format: jb-book
root: intro
chapters:
- file: _sources/Week_01 # Introduction to Data Science
  sections:
  - url: https://docs.google.com/presentation/d/1cQJycGyQ07qSOoeskr6GjjTD3byIkxDbdi228NRgFeU/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/JupyterNumpy
  - file: _sources/lectures/Pandas
  - file: _sources/lectures/Visualization
  - file: _sources/lectures/Clustering
  - file: _sources/lectures/Dimensionality
  - file: _sources/lectures/Nonlinear
  - file: _sources/homework/Homework_01
- file: _sources/Week_02 # Probability Theory and Density Estimation
  sections:
  - url: https://docs.google.com/presentation/d/1o9tM9ppKZWIa9B3WIHy5JDF4myR5NkO02W6WAlyiTSg/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/ProbabilityTheory
  - file: _sources/lectures/ProbabilityDistributions
  - file: _sources/lectures/DensityEstimation
  - file: _sources/homework/Homework_02
- file: _sources/Week_03 # Bayesian Statistics I
  sections:
  - url: https://docs.google.com/presentation/d/1h2SMuH-Z5a_OE6UMDbFjysEiL2NmYT1tGww6VF5jzsA/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/Statistics
  - file: _sources/lectures/BayesianInference
  - file: _sources/lectures/MarkovChainMonteCarlo
  - file: _sources/lectures/MarkovChains
  - file: _sources/homework/Homework_03
- file: _sources/Week_04 # Bayesian Statistics II
  sections:
  - url: https://docs.google.com/presentation/d/18bft9_CiBLjjBy0MHvT_vN7E95kfakvhm_7d7WKHXyY/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/ModelSelection
  - file: _sources/lectures/VariationalInference
  - file: _sources/lectures/NormalizingFlows
  - file: _sources/lectures/SimulationBasedInference
  - file: _sources/homework/Homework_04
- file: _sources/Week_05 # Introduction to Artificial Intelligence and Machine Learning
  sections:
  - url: https://docs.google.com/presentation/d/1by3-6jDEorKi7_WEr6PTMfEBE8f4xrS94fNdtSuATVg/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/Learning
  - file: _sources/lectures/Optimization
  - file: _sources/lectures/CrossValidation
  - file: _sources/lectures/SupervisedLearning
  - file: _sources/lectures/ArtificialNeuralNetworks
  - file: _sources/homework/Homework_05
- file: _sources/Week_06 # Deep Learning and Generative Modeling
  sections:
  - url: https://docs.google.com/presentation/d/1h13YeUjtTU_WHLxghxFBBQJO3uRr1GtsIyO4DVZviJo/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/DeepLearning.ipynb
  - file: _sources/lectures/GenerativeModeling.ipynb
- file: _sources/Week_07 # Convolutional and Recurrent Neural Networks
  sections:
  - url: https://docs.google.com/presentation/d/1cDFVtEVGLaWd4256OShSb3Roto0x4y4GwG6LkhVozg0/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/ConvolutionalRecurrentNeuralNetworks
  - file: _sources/homework/Homework_06
- file: _sources/Project_01 # Project 01
  sections:
  - file: _sources/projects/Project_01_HiggsTauTau
  - file: _sources/projects/Project_01_ExoticParticles
  - file: _sources/projects/Project_01_GalaxyZoo
  - file: _sources/projects/Project_01_NuclearGeometryQGP
  - file: _sources/projects/Project_01_AberratedImages
  - file: _sources/projects/Project_01_DarkEnergySurvey
- file: _sources/Week_08 # Geometric Deep Learning and Graph Neural Networks
  sections:
  - url: https://docs.google.com/presentation/d/1jK61M3QGH7bxFU7TMBm16G3YDb-7HOFtgNdqlj3Gs38/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/GraphNeuralNetworks
- file: _sources/Week_09 # Attention Mechanism and Transformers
  sections:
  - url: https://docs.google.com/presentation/d/1ZHuK7TopASFSoyUoELKeCGT8bullhtSLcEkrp4ZueGg/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/AttentionTransformers
- file: _sources/Week_10 # Reinforcement Learning
  sections:
  - url: https://docs.google.com/presentation/d/1EsW71u3hdNdXyhlDfkmOX__9c4wJZUee_pjlsmlv_Vg/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/ReinforcementLearning
  - file: _sources/homework/Homework_07
- file: _sources/Week_11 # AI Explainability and Uncertainty Quantification
  sections:
  - url: https://docs.google.com/presentation/d/1ydzY7IEYzALTR6ez5gvwwKDduf_7wUtZddq0SUSuvI0/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/AIExplainabilityUncertaintyQuantification
  - file: _sources/homework/Homework_08
- file: _sources/Week_12 # Unsupervised Learning and Anomaly Detection
  sections:
  - url: https://docs.google.com/presentation/d/1ydzY7IEYzALTR6ez5gvwwKDduf_7wUtZddq0SUSuvI0/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/UnsupervisedLearningAnomalyDetection
- file: _sources/Week_13 # Physics Informed Neural Networks
  sections:
  - url: https://docs.google.com/presentation/d/1C-Z8b6WP5rE8yohZQdSxyH8O_bHIbllq97QhEJYyh0w/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/PhysicsInformedNeuralNetworks
  - file: _sources/lectures/LearningTheSchrodingerEquation
  - file: _sources/lectures/SymbolicRegression
- file: _sources/Project_02 # Project 02
  sections:
  - file: _sources/projects/Project_02_AnisotropyQGP
  - file: _sources/projects/Project_02_AberratedImages
  - file: _sources/projects/Project_02_GravitationalWaves
- file: _sources/Week_14 # Learning from the Machines
  sections:
  - url: https://docs.google.com/presentation/d/1hkfaU7JVy1f5S8jURZvTY67KRzP7I8zGRf4Zku_bpM4/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/LearningPhysicsMachines
- file: _sources/Week_15 # Future of Physics: What Lies Ahead?
  sections:
  - url: https://docs.google.com/presentation/d/1eB1qCn5J07D5he_DCpkBiKjbVjdI6OexUzMQ351GCaI/edit?usp=sharing
    title: Slides
  - file: _sources/lectures/LookingForward