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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 course, we will use machine learning to build a value estimation system that can deduce the value of a home. Although the tool we will build in this course focuses on real estate, you can use the same approach to solve any kind of value estimation.
What you’ll learn include:
- Basic concepts in machine learning
- Supervised versus Unsupervised learning
- Machine learning frameworks
- Machine learning using Python and scikit-learn
- Loading sample dataset
- Making predictions based on dataset
- Setting up the development environment
- Building a simple home value estimator
The examples in this course are basic but should give you a solid understanding of the power of machine learning and how it works.
- Absolute beginners to Machine Learning
|Setting Up Test Environment|
|What is Python?||00:00:00|
|Machine Learning Basics|
|What is Machine Learning||00:00:00|
|Machine Learning Frameworks||00:00:00|
|Machine Learning Vocabulary||00:00:00|
|Supervised Machine Learning||00:00:00|
|Where Machine Learning is Used||00:00:00|
|Creating a basic house value estimator||00:00:00|
|Loading a Dataset Part 1||00:00:00|
|Loading a Dataset Part 2||00:00:00|
|Making predictions – Part 1||00:00:00|
|Making predictions – Part 2||00:00:00|
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