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Introduction to Regression with statsmodels in Python

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Course Features

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Duration

4 hours

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Delivery Method

Online

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Available on

Limited Access

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Accessibility

Mobile, Desktop, Laptop

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Language

English

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Subtitles

English

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Level

Beginner

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Teaching Type

Self Paced

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Video Content

4 hours

Course Description

Logistic regression and linear regression are two of the most common statistical models. These models are master keys to unlocking the secrets of your data. This course will show you how to solve simple linear and logistic regressions. This course will teach you how to analyze relationships between variables using real-world data. This covers motor insurance claims, Taiwan house prices, fish sizes, as well as other topics. By the end of this course, you will be able use your data to make predictions and measure model performance.

Course Overview

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Virtual Labs

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International Faculty

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Post Course Interactions

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Hands-On Training,Instructor-Moderated Discussions

Skills You Will Gain

Prerequisites/Requirements

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Introduction to Data Visualization with Seaborn

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Introduction to Statistics in Python

What You Will Learn

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Predict housing prices and ad click-through rate by implementing, analyzing, and interpreting regression analysis in Python

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Through hands-on exercises, you’ll explore the relationships between variables in real-world datasets, including motor insurance claims, Taiwan house prices, fish sizes, and more

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By the end of this course, you’ll know how to make predictions from your data, quantify model performance, and diagnose problems with model fit

Course Instructors

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Maarten Van den Broeck

Content Developer at DataCamp

Maarten is an aquatic ecologist and teacher by training and a data scientist by profession. After his career as a Ph.D. researcher at KU Leuven, he wished that he had discovered DataCamp sooner. He l...

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Course Cover

$12

$6

49% OFF

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