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Data Analytics

In this course, we introduce the tools and techniques for data analytics. We examine statistical, machine learning, data mining and data management techniques that make possible the efficient analysis of data. Students are expected to have a good overview of data analytics techniques from the management, manipulation, analysis, and interpretation. Techniques, issues, and challenges will also be covered for big data.

Assignment

Please find datasets from Kaggle, Github, etc. in preparation for the assignment.

1

Welcome Pack

1) Course Outline

2

Simple Linear Regression

2) Dataset Example 1

3) Python codes for Example 1

3

Multiple Linear Regression

2) Dataset Example 2

3) Python codes for Example 2

4) Dataset Example 4

4

Logistic Regression

1) Slide - Introduction to Classification Techniques

2) Slide - Logistic Regression

3) GLOW Dataset

4) Python codes for GLOW500

5

Naive Bayes

1) Slide - Naive Bayes

2) Data set - Example 5

3) Example 5 - Python codes

4) Dataset - Bank

5) Bank - Python codes

6) Dataset - Loan

7) Loan - Python codes

6

Linear Discriminant Analysis

1) Slide - Linear Discriminant Analysis

2) Data set - Example 2

3) Example 2 - Python codes

4) Dataset - Example 3

5) Example 3 - Python codes

7

Dimensionality Reduction Methods

1) Slide Dimensional Reduction

2) Dataset USArrest

3) Python code - SVD - Example 1

4) Python code - SVD - USArrest

5) Python code - SVD - Image Example 1

6) Data Image 1

7) Python code - PCA - USArrest

Link online Class (8pm-10pm)

8

k Nearest Neighbors

2) Dataset Example 5

3) Python code - KNN - Example 5

4) Dataset Cancer

5) Python code - KNN - Data Cancer

Link online Class (8pm-10pm)

9

Support Vector Machine

2) Python code - Example 1

3) Python code - Example 2

Link online Class (8pm-10pm)

10

Decision Trees

1) Slide Classification and Regression Trees

2) Python code - Example 1 - Classification Trees

3) Data set Hitters.csv

4) Data set Heart Disease - processed.cleveland.data

5) Python code - Example 2 - Heart Disease (complete guide)

6) Python code - Bagging, Random Forest and Boosting

11

Clustering

1) Slide Clustering.

2) Python code - KMeans and Hierarchical Clustering

3) Python code - Clustering using NC160 Dataset

12

Discussion Past Questions

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