Data Modeling
20
Lessons
1
Videos
All
Skill Level
8 Hours
Duration
English
Language
Set Up & Introduction
If you don’t have your environment set up yet. Please reference this guide. Throughout this lesson we’ll make use of multiple Python libraries. If you see a library you haven’t previously used, simply install the library using pip install. For reference, here’s the pip install documentation.
The next concept we’ll be going over is modeling our data. Even though modeling data is extremely important, it’s important to understand that a majority of your time will be spent cleaning and exploring your data and thus, should be practiced heavily. In this series, we’ll go over some commonly used models, how they work, how to implement them, and when to use them. Feel free to use your own datasets when following along.
Completing this course will help you:
- Understand MYSQL and Related Languages
- Pull information from structured databases
- Improve your knowledge of syntax
Who is the course for?
Learning Path
Before we start learning how to use models, it’s important to understand what it means to “train” and “test” in the context of machine learning. When you “train” your model, you are fitting your model to a part of your dataset.
“Querying” a database is another way of saying you want to “retrieve information from” a database. SQL queries make use of a powerful command called SELECT, it allows us to retrieve specific information from our database.
Cross-Validation is a method to reduce overall bias in our model’s predictions.
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