Slides
Lecture_2_2 : Recommender System; Clustering (Video, pwd:Y72A1$?P)
Lecture_3_1 : Neural Network I (Video, pwd:f!AL2mc5)
Lecture_3_2: Neural Network II
Lecture_3_3: Neural Network III
Notebooks
Multivariate Linear Regression
Real life examples | ![]() |
To model and reveal the force of gravity | ![]() |
2D function fitting | ![]() |
Gradient Descent & Conjugate Gradient | ![]() |
Logistic Regression
Real life examples | ![]() |
Example on grade weighting | ![]() |
Fisher's Iris | ![]() |
Support Vector Machine
Fermi surface | ![]() |
Real life examples | ![]() |
Fisher's Iris | ![]() |
Principal Component Analysis
Real life examples | ![]() |
Ising model | ![]() |
Clustering
Real life examples | ![]() |
Ising model | ![]() |
Neural Network
Perceptron | ![]() |
Neural network in Fisher's Iris classification | ![]() |
Back propagation_wheat-seeds | ![]() |
MNielsen network | ![]() |
Feedforward Neural Network | ![]() |
Supplemental Materials
1. Handwritten notes on SVM | SVM |
2. Mean field hubbard model on square lattice An example on solving ground state energy using gradient descent method |
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3. Handwritten notes on 2D Ising model | Ising model |
4. Handwritten notes on Neural Network | Feed-forward&Back-propagation |