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Lazy Predict All Models in One Go

BeginnerGuided Project

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.

4.5 (29 Reviews)

Language

  • English

Topic

  • Data Science

Industries

  • Banking, Retail

Enrollment Count

  • 185

Skills You Will Learn

  • Python, Machine Learning, Data Science, AutoML

Offered By

  • IBMSkillsNetwork

Platform

  • SkillsNetwork

Last Update

  • May 17, 2024
About This Guided Project

Why you should do this Guided Project

As machine learning becomes more prominent in various fields - ranging from healthcare to retail - being able to utilize it is a valuable asset. Conveniently, a new subfield of machine learning has emerged: automated machine learning. Designed for non-experts, it automatically runs a variety of models under a certain category and compares their performance. Go from zero to hero! 


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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

After completing this lab, you will be able to:
  1. Understand what AutoML is
  2. Apply "LazyPredict" to classification and regression problems
  3. Evaluate models' performance from "LazyPredict"

What You'll Need

This project uses JupyterLab. Although general knowledge about data wrangling is recommended to take advantage of automated ML,  this project is designed for beginners with no prior experience in coding machine learning models. Also note that this platform works best with current versions of Chrome, Edge, Firefox, Internet Explorer or Safari.

Instructors

Cindy Huang

Data Science Intern at IBM

Hey there! I'm a senior at the University of Toronto studying data science. My passion for machine learning lies in NLP and using technology to improve human experience.

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Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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Contributors

Roxanne Li

Data Scientist at IBM

I am an aspiring Data Scientist at IBM with extensive theoretical/academic, research, and work experience in different areas of Machine Learning, including Classification, Clustering, Computer Vision, NLP, and Generative AI. I've exploited Machine Learning to build data products for the P&C insurance industry in the past. I also recently became an instructor of the Unsupervised Machine Learning course by IBM on Coursera!

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