Machine Learning Python: Regression Modeling

Simpliv

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Online

£ 10 + VAT

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Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

Use Linear Regression to solve business problems and master the basics of Machine LearningThe 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 PythonThis course is suitable for anyone curious about machine learning or professionals beginning their data journey.

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

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

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This centre's achievements

2021

All courses are up to date

The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 4 years

Subjects

  • Statistics
  • Interpreting

Course programme

Introduction 2 lectures 08:06 Welcome to the course! Course contents Introduction 2 lectures 08:06 Welcome to the course! Course contents Welcome to the course! Welcome to the course! Welcome to the course! Welcome to the course! Course contents Course contents Course contents Course contents Basics of Statistics 5 lectures 30:10 Types of Data Types of Statistics Describing data Graphically Measures of Centers Measures of Dispersion Basics of Statistics 5 lectures 30:10 Types of Data Types of Statistics Describing data Graphically Measures of Centers Measures of Dispersion Types of Data Types of Data Types of Data Types of Data Types of Statistics Types of Statistics Types of Statistics Types of Statistics Describing data Graphically Describing data Graphically Describing data Graphically Describing data Graphically Measures of Centers Measures of Centers Measures of Centers Measures of Centers Measures of Dispersion Measures of Dispersion Measures of Dispersion Measures of Dispersion Setting up Python and Jupyter Notebook 9 lectures 01:38:02 Installing Python and Anaconda Opening Jupyter Notebook Introduction to Jupyter Arithmetic operators in Python: Python Basics Strings in Python: Python Basics Lists, Tuples and Directories: Python Basics Working with Numpy Library of Python Working with Pandas Library of Python Working with Seaborn Library of Python Setting up Python and Jupyter Notebook 9 lectures 01:38:02 Installing Python and Anaconda Opening Jupyter Notebook Introduction to Jupyter Arithmetic operators in Python: Python Basics Strings in Python: Python Basics Lists, Tuples and Directories: Python Basics Working with Numpy Library of Python Working with Pandas Library of Python Working with Seaborn Library of Python Installing Python and Anaconda Installing Python and Anaconda Installing Python and Anaconda Installing Python and Anaconda Opening Jupyter Notebook Opening Jupyter Notebook Opening Jupyter Notebook Opening Jupyter Notebook Introduction to Jupyter Introduction to Jupyter Introduction to Jupyter Introduction to Jupyter Arithmetic operators in Python: Python Basics Arithmetic operators in Python: Python Basics Arithmetic operators in Python: Python Basics Arithmetic operators in Python: Python Basics Strings in Python: Python Basics Strings in Python: Python Basics Strings in Python: Python Basics Strings in Python: Python Basics Lists, Tuples and Directories: Python Basics Lists, Tuples and Directories: Python Basics Lists, Tuples and Directories: Python Basics Lists, Tuples and Directories: Python Basics Working with Numpy Library of Python Working with Numpy Library of Python Working with Numpy Library of Python Working with Numpy Library of Python Working with Pandas Library of Python Working with Pandas Library of Python Working with Pandas Library of Python Working with Pandas Library of Python Working with Seaborn Library of Python Working with Seaborn Library of Python Working with Seaborn Library of Python Working with Seaborn Library of Python Introduction to Machine Learning 2 lectures 24:46 Introduction to Machine Learning Building a Machine Learning Model Introduction to Machine Learning 2 lectures 24:46 Introduction to Machine Learning Building a Machine Learning Model Introduction to Machine Learning Introduction to Machine Learning Introduction to Machine Learning Introduction to Machine Learning Building a Machine Learning Model Building a Machine Learning Model Building a Machine Learning Model Building a Machine Learning Model Data Preprocessing 17 lectures 02:01:22 Gathering Business Knowledge Data Exploration The Dataset and the Data Dictionary Importing Data in Python Univariate analysis and EDD EDD in Python Outlier Treatment Outlier Treatment in Python Missing Value Imputation Missing Value Imputation in Python Bi-variate analysis and Variable transformation Variable transformation and deletion in Python Non-usable variables Dummy variable creation: Handling qualitative data Dummy variable creation in Python Correlation Analysis Correlation Analysis in Python Data Preprocessing ng Simple Linear Regression in Python Simple Linear Regression in Python Simple Linear Regression in Python Simple Linear Regression in Python Multiple Linear Regression Multiple Linear Regression Multiple Linear Regression Multiple Linear Regression The F - statistic The F - statistic The F - statistic The F - statistic Interpreting results of Categorical variables Interpreting results of Categorical variables Interpreting results of Categorical variables Interpreting results of Categorical variables Multiple Linear Regression in Python Multiple Linear Regression in Python Multiple Linear Regression in Python Multiple Linear Regression in...

Additional information

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

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