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Logistic Regression in Python
This course will focus on providing exposure to building a logistic regression model and interpreting the results of the model as well.
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2 Videos
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1 Coding Case
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2 Readings
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1 Quiz
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Difficulty: Intermediate
Foundational knowledge or experience in statistics or analytics is recommended.
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Duration: Approximately 4 hours
Course Overview
- Logistic regression is one of the most popular and widely used regression techniques in statistics and machine learning, widely used across industry domains and verticals.
- This robust technique is often used to describe the relationship between a binary predicted variable and a set of predictor variables.
- Learn the theoretical concepts behind logistic regression and build and evaluate a robust model on a real-world dataset to solve a business objective.
- Gain practical experience by applying the coding skills and understanding on real-world business scenarios.
What’s included
Flexible Scheduling
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Desktop Only
We recommend completing this project on a desktop
Skills You Will Learn
Associated Learning Tracks
How it Works
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With our hands-on projects, you will take your newly learned skills along with our 750+ low-code/no-code functions and embedded coding console to complete milestone-based projects. Once completed, you will have effectively applied new skills and concepts to real-world data cases that can be translated directly into your career.
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Rolai’s patented process provides a personalized learning process for each user. Rolai goes deeper than simply learning concepts and testing your skills. At Rolai, learners can apply their skills to actual industry use cases and projects.
Our courses include readings, videos, quizzes, and hands-on data cases that are completed using our virtual lab; give learners an applied learning experience.
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