Lazy Predict All Models in One Go
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Streamline your machine learning workflow with Lazy Predict. Learn how to quickly test multiple models, evaluate their performance, and select the best algorithm for your data without extensive coding or manual tuning.
At a Glance
Automated Machine Learning (AutoML) is a field of machine learning that automates many monotonous tasks of Machine learning. You can go from zero to hero with some basic Machine Learning knowledge and Python programming skills. In this project, you will explore “LazyPredict,” a semi-automated ML library used to build many popular models using two simple lines of code; you will apply your knowledge to predict flight delays and admissions probability.
Why you should do this Guided Project
In this guided project, you will learn to use “LazyPredict”, a semi-automated ML library for machine learning tasks. Specifically, you will use it to predict for two real-life scenarios: 1) whether a flight will be delayed and 2) the chances of admissions to university.
A Look at the Project Ahead
- Understand what AutoML is
- Apply “LazyPredict” to classification and regression problems
- Evaluate models’ performance from “LazyPredict”
What You’ll Need
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