[Lynda] Machine Learning & AI Foundations: Value Estimations
Machine Learning & AI Foundations: Value Estimations

Machine Learning & AI Foundations: Value Estimations

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Course Description

Value estimation—one of the most common types of machine learning algorithms—can automatically estimate values by looking at related information. For example, a website can determine how much a house is worth based on the property's location and characteristics. In this project-based course, discover how to use machine learning to build a value estimation system that can deduce the value of a home. Follow Adam Geitgey as he walks through how to use sample data to build a machine learning model, and then use that model in your own programs. Although the project featured in this course focuses on real estate, you can use the same approach to solve any kind of value estimation problem with machine learning.

What you will learn

Setting up the development environment Building a simple home value estimator Finding the best weights automatically Working with large data sets efficiently Training a supervised machine learning model Exploring a home value data set Deciding how much data is needed Preparing the features Training the value estimator Measuring accuracy with mean absolute error Improving a system Using the machine learning model to make predictions


Section 1: Introduction

Section 2: 1. What Is Machine Learning and Value Prediction?

Section 3: 2. An Overview of Building a Machine Learning System

Section 4: 3. Training Data

Section 5: 4. Features

Section 6: 5. Coding Our System

Section 7: 6. Improving Our System

Section 8: 7. Using the Estimator in a Real-World Program

Section 9: Conclusion