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Use Linear Regression to solve business problems and master the basics of Machine<br>Learning<br>The course "Machine Learning Basics: Building Regression Model in Python" teaches you all<br>the steps of creating a Linear Regression model, which is the most popular Machine Learning<br>model, to solve business problems.<br>In this course students will learn the following:<br>u2022 How to predict future outcomes basis past data by implementing Simplest Machine Learning<br>algorithm<br>u2022 How to do preliminary analysis of data using Univariate and Bivariate analysis before running<br>Linear regression<br>u2022 Understand how to interpret the result of Linear Regression model and translate them into<br>actionable insight<br>u2022 Understanding of basics of statistics and concepts of Machine Learning<br>u2022 Learn advanced variations of OLS method of Linear Regression<br>u2022 Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries<br>of Python<br>This course is suitable for anyone curious about machine learning or professionals beginning<br>their data journey.
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Machine Learning Python: Regression Modeling Linear Regression Model Use Linear Regression to solve business problems and master the basics of Machine Learning The course "Machine Learning Basics: Building Regression Model in Python" teaches you all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems. In this course students will learn the following: How to predict future outcomes basis past data by implementing Simplest Machine Learning algorithm • How to do preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression • 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 •
Learn advanced variations of OLS method of Linear Regression • Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python • This course is suitable for anyone curious about machine learning or professionals beginning their data journey. Basic knowledge: Students will need to install Python and Anaconda software but we have a separate lecture to help you install the same • What will you learn: In this course students will learn the following: How to predict future outcomes basis past data by implementing Simplest Machine Learning algorithm • How to do preliminary analysis of data using Univariate and Bivariate analysis before running Linear regression • 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 • Learn advanced variations of OLS method of Linear Regression • Linear Regression technique of Machine Learning using Scikit Learn and Statsmodel libraries of Python • Course Curriculum: Number of Lectures: 51 Total Duration: 07:13:43 Introduction 2 lectures Basics of Statistics 5 lectures Setting up Python and Jupyter Notebook 9 lectures Introduction to Machine Learning 2 lectures Data Preprocessing 17 lectures Linear Regression 16 lectures Course Link: https://www.simpliv.com/machinelearning/machine-learning-basics- regression-modeling-in-python
