Applied-Machine-Learning

Overview

This repository contains my work and solutions for the Applied Machine Learning course offered by Centre College in the Spring of 2023. The course covers data science and advanced analytic tools, working with clients, exploratory data analysis, data preparation, model building, various machine learning methods, result analysis, and presentations using data visualization tools.

Table of Contents

1. Introduction
2. Learning Outcomes
3. My Assignments

Introduction

The Applied Machine Learning course offers an introduction to data science and advanced analytic tools. It covers the following topics:

• Data analytics lifecycle
• Data analytics tools
• Exploratory data analysis
• Data preparation
• Machine learning methods
• Result analysis
• Data visualization

Learning Outcomes

Upon completion of this course, students should be able to:

• Describe the work of a data scientist
• Understand and apply the data analytics lifecycle
• Use a variety of data analytics tools
• Work with varied data sets
• Perform exploratory data analysis
• Prepare data for model building -Describe and distinguish several methods used to model data
• Model data using appropriate machine learning methods -Analyze and assess analytic results
• Present results orally and in writing with the help of data visualization tools

My Assignments

This repository contains my solutions to the assignments for this course. Please find the links to the assignments below:

• P0: Jupyter, Python, EDA, Pandas import CSV, basic stats, Matplotlib, scatter
• P1: Getting Started
• P2: Wine Reviews
• P3: Customer Churn
• P4: Dry Beans
• P5: Image Segmentation and Compression
• Final Project