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General

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Course Outline

ABW505 Class Slot (Tuesday OR Friday)

ABW505: Coursework Grade (40%)

ABW505-CW grade (40%)

Attendance

Group Projects (50%)

Group Projects - Briefing Video

Group Project 1 (20%)

Group Project 2 (30%)

Mid-Term Test

Midterm Test

Introduction to Machine Learning

Lesson 1 - Slide

Lesson 1 - Recorded Video

Introduction

Lesson 2 - Slide

Lesson 2 - Recorded Video

Core Objects, Variables, Input and Output

Lesson 3 - Slide

Lesson 3 - Recorded Video and Simple Hands-On

Structures that Control Flow

Lesson 4 - Control Flow Structures-Part 1- Conditional Statements

Lesson 4 - Recording Link

Lab Activity-Part1

Lab Activity1 Answers

Lesson 5 - Control Flow Structure- Part2

Lists, Tuples, and Dictionaries

Lesson 6 - Lists, Tuples, and Dictionaries

Lab Activity 3

Functions

Lesson 7 - Functions

Lesson 8 - Function Class Recording

Lab Activity 4

Numpy, Pandas and Matplotlib

Lesson 9 - Slide - Introduction to Python NumPy, Pandas, and Matplotlib

Datasets

Lab Activity 5

Lab Activity 6

Lab Activity 7 - Iris

Dataset: Iris

K-Nearest Neighbors

Lesson 10 - Slide

Lesson 10 - Recorded Video

Lesson 10 - Hands-On Video

Sample Code

dataset

real dataset

EXTRA - Feature Selection Sample Code

EXTRA - Hands-on Recording Link

Dataset - train_fs

Dataset - Iris

Decision Trees

Lesson 11 - Slide

Lesson 11 - Recorded Video

Dataset

Dataset_Real

Sample Code

Naive Bayes and Support Vector Machine

Lesson 12 - Slide

Lesson 12 - Recorded Video

Hands-On Naive Bayes &amp; SVM

Hands-On Dataset

Naive Bayes and SVC Code - Solution

Hands-On Recording Video Link

EXTRA - Naive Bayes Sample Code

Train Dataset - Titanic700

Test Set - Titanic192

Lab Activity 8

Clustering

Lesson 13 - Slide

Lesson 13 - Recorded Video Part 1

Lesson 13 - Recorded Video Part 2

Lesson 13 - Recorded Video Part 3

Ensemble Method and Random Forest

Lesson 14 - Slide Part 1

Lesson 14 - Slide Part 2

Lesson 14 - Recorded Video Part 1

Hands-On Naive Bayes & SVM