Machine Learning and AI Foundations: Value Estimations

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Adam Geitgey

1:04:55

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01 - Introduction

01 - Welcome.mp4

00:42

02 - What you should know.mp4

00:21

03 - Using the exercise files.mp4

00:31

04 - Set up the development environment.mp4

02:21

02 - 1. What Is Machine Learning and Value Prediction

01 - What is machine learning.mp4

03:11

02 - Supervised machine learning for value prediction.mp4

02:45

03 - Build a simple home value estimator.mp4

02:37

04 - Find the best weights automatically.mp4

04:07

05 - Cool uses of value prediction.mp4

02:06

03 - 2. An Overview of Building a Machine Learning System

01 - Introduction to NumPy, scikit-learn, and pandas.mp4

01:22

02 - Think in vectors How to work with large data sets efficiently.mp4

02:58

03 - The basic workflow for training a supervised machine learning model.mp4

02:22

04 - Gradient boosting A versatile machine learning algorithm.mp4

03:55

04 - 3. Training Data

01 - Explore a home value data set.mp4

02:56

02 - Standard conventions for naming training data.mp4

00:53

03 - Decide how much data you need.mp4

02:04

05 - 4. Features

01 - Feature engineering.mp4

04:11

02 - Choose the best features for home value prediction.mp4

03:19

03 - Use as few features as possible The curse of dimensionality.mp4

01:50

06 - 5. Coding Our System

01 - Prepare the features.mp4

01:48

02 - Training vs. testing data.mp4

01:03

03 - Train the value estimator.mp4

02:51

04 - Measure accuracy with mean absolute error.mp4

01:31

07 - 6. Improving Our System

01 - Overfitting and underfitting.mp4

02:44

02 - The brute force solution Grid search.mp4

02:46

03 - Feature selection.mp4

02:26

08 - 7. Using the Estimator in a Real-World Program

01 - Predict values for new data.mp4

02:39

02 - Retrain the classifier with fresh data.mp4

01:48

09 - Conclusion

01 - Wrap-up.mp4

00:48

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.

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Artificial Intelligence

Programming Fundamentals

Adam Geitgey

Instructor's Courses

Co-founder at Turquoise Health, previously AI/ML/NLP Consultant and a Software Engineer with 15+ years of experience. Writes about Machine Learning, AI and Software Engineering at http://www.machinelearningisfun.com/

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