Complete Linear Regression Analysis in Python

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  1. admin

    admin Administrator Staff Member


    [​IMG]
    Complete Linear Regression Analysis in Python

    ★★★★☆
    $29.99
    $13.00 in stock
    Enroll Now
    [​IMG] Udemy.com
    as of

    Linear Regression in Python| Simple Regression, Multiple Regression, Ridge Regression, Lasso and subset selection also

    [​IMG]
    Created by: Start-Tech Academy
    1,700,000+ Enrollments | 4+ Rated | 160+ Countries
    Rating: 4.33 (785 reviews) 95294 students enrolled
    What Will I Learn?

    • Learn how to solve real life problem using the Linear Regression technique
    • Preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression
    • Predict future outcomes basis past data by implementing Simplest Machine Learning algorithm
    • Understand how to interpret the result of Linear Regression model and translate them into actionable insight
    • Understanding of basics of statistics and concepts of Machine Learning
    • Indepth knowledge of data collection and data preprocessing for Machine Learning Linear Regression problem
    • Learn advanced variations of OLS method of Linear Regression
    • Course contains a end-to-end DIY project to implement your learnings from the lectures
    • How to convert business problem into a Machine learning Linear Regression problem
    • Basic statistics using Numpy library in Python
    • Data representation using Seaborn library in Python
    • Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python
    Requirements

    • Students will need to install Python and Anaconda software but we have a separate lecture to help you install the same
    Target audience

    • People pursuing a career in data science
    • Working Professionals beginning their Data journey
    • Statisticians needing more practical experience
    • Anyone curious to master Linear Regression from beginner to Advanced in short span of time

    Continue reading...
     


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