lab challenge

Machine Learning Python Challenge: Regression

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1h 30m
108
3/5
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Lab description

In this lab challenge, you will be tested on your scikit-learn skills to build a machine learning pipeline to predict the price of a stock. Here, you will be tested on data preprocessing, fitting, and evaluation of the regression model. 

To get the most from this lab, it is recommended to have confidence and exposure to at least the following libraries: pandas, matplotlib and scikit-learn.

You are strongly encourage to have completed the following courses, available in our content library:

as well as the following lab:

before starting this challenge.

Updates

April 6ht, 2023 - Resolved a dependency issue causing the stock ticker data frame 

January 27th, 2022 - Updated Python libraries to resolve an issue using the Yahoo APIs

September 20th, 2021 - Updated Python libraries to resolve an issue using the Yahoo APIs

Prerequisites
  • Knowledge of regression: Completion of the Building a Machine Learning pipeline with scikit-learn: part 02 course is highly recommended
  • Knowledge of preprocessing: Completion of the Building a Machine Learning pipeline with scikit-learn: part 01 course is highly recommended
Intended audience
  • Machine Learning Engineers
  • Data scientists
What will be assessed
  • Your ability to create a machine learning pipeline
  • Your ability to fit a linear regression model
  • Your ability to evaluate a fitted model
About the author
Avatar
Andrea Giussani
Data Scientist
Students
5,653
Labs
13
Courses
8
Learning paths
6

Andrea is a Data Scientist at Cloud Academy. He is passionate about statistical modeling and machine learning algorithms, especially for solving business tasks.

He holds a PhD in Statistics, and he has published in several peer-reviewed academic journals. He is also the author of the book Applied Machine Learning with Python.

Covered topics
Mission
Machine Learning Challenge: Regression