Home / Lectures | Data Mining

Ferdowsi University of Mashhad, Spring 2023

Mahmood Amintoosi

m.amintoosi@um.ac.ir

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Welcome to the Course!

Lectures

Week01 - Introduction

1: Instructor’s personal page
2: Python Data Science Handbook
3: Python Data Science Handbook’s codes
4: References

Week02 - Data Science with python

1

Python Data Science Handbook: section 2.02, section 2.03

2

HWUS Presidents’ Height

Week03 - Neural Networks

1

Application of Taylor’s expansion in reducing the volume of convolutional neural network: up to section 3.2

2

Introduction to PyTorch

3

Python Data Science Handbook: section 5.00, section 5.01, section 5.02

Week04 - KNN Classification

1

Python Data Science Handbook: section 5.01, section 5.02, section 5.03

2

A comparison of several classifiers in scikit-learn

3

Code KNN-Iris

4

Code KNN-mnist

5

HWHand Written digits Recognition

Week05 - K-means Clustering

1

K-means from the ESL book: section 14.3.6

2

K-means Clustering: section 8.3

3

Python Data Science Handbook: section 5.11

Week06 - Regression/ Logistic Regression

1: Code PyTorch
2: Code Regression - Gradient Descent
3: HWImplementation of Gradient Descent
4: Code Regression - Vectorized
5: Code Logistic Regression
6: HWLogistic Regression

Week06 - Bayes Method

1

Bayesian Classification: up to page 17

2

A simple explanation of Naive Bayes Classification: The highest score answer

Week06 - Clustering Methods Validation

1

Linear Discriminant Analysis: up to page 12

Week07 - Dimension reduction (Principal Component Analysis)

1: Principal Component Analysis explained visually (setosa.io)
2: PCA slides from Bishop’s book
3: CodePCA
4: In Depth: Principal Component Analysis

Week08 - Linear Discriminant Analysis

1

Clustering Validation: up to page 10

2

HWLDA Algorithm Implementation

Week08 - Weighted KNN

1: Classifier implementing the k-nearest neighbors vote

Week08 - Recommendation Systems

1

Collaborative Filtering: unit 2

2

Item Based Filtering: unit 3 - up to page 81

Week09 - Decision Tree

1

Entropy (information theory) (wikipedia)

2

Decision tree slides: up to page 20

3

HWGolf Game Decision Tree

4

HWCompletion of the decision tree program

5

In-Depth: Decision Trees and Random Forests

6

HWClassification of Persian Hoda digits with random forest

Week10 - Frequent Item-set Mining

1

Itemset Mining: up to page 17

2

Code FIM

Week11 - EM & GMM

1

Relation between kmeans and GMM: The second answer

2

In Depth: Gaussian Mixture Models

Week11 - Mahalanobis distance

1: Reminder of PCA and covariance matrix topic
2: What is the covariance matrix and what are its uses?
3: Explanation of the Mahanalobis distance
4: What is Mahalanobis distance?
5: Normal distribution (Wikipedia)