Machine Learning Basics: Classification models in R

Simpliv

Course

Online

£ 10 VAT inc.

The best Other Education courses

See all

See all

Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

You're looking for a complete Classification modelling course that teaches you everything you need to create a Classification model in R, right?You've found the right Classification modelling course!After completing this course, you will be able to:· Identify the business problem which can be solved using Classification modelling techniques of Machine Learning.Create different Classification modelling model in R and compare their performance.
Confidently practice, discuss and understand Machine Learning conceptsHow this course will help you?A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course.If you are a business manager or an executive, or a student who wants to learn and apply machine learning in Real world problems of business, this course will give you a solid base for that by teaching you the most popular Classification techniques of machine learning, such as Logistic Regression, Linear Discriminant Analysis and KNNWhy should you choose this course?This course covers all the steps that one should take while solving a business problem using classification techniques.Most courses only focus on teaching how to run the analysis but we believe that what happens before and after running analysis is even more important i.e. before running analysis it is very important that you have the right data and do some pre-processing on it. And after running analysis, you should be able to judge how good your model is and interpret the results to actually be able to help your business.What makes us qualified to teach you?The course is taught by Abhishek and Pukhraj. As managers in Global Analytics Consulting firm, we have helped businesses solve their business problem using machine learning techniques and we have used our experience to include the practical aspects of data analysis in this course
tually is. It also contains steps involved in building a machine learning model, not just...

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

Understand how to interpret the result of Logistic Regression model and translate them into actionable insight
Learn the linear discriminant analysis and K-Nearest Neighbors technique
Learn how to solve real life problem using the different classification techniques
Preliminary analysis of data using Univariate analysis before running classification model
Predict future outcomes basis past data by implementing Machine Learning algorithm
Indepth knowledge of data collection and data preprocessing for Machine Learning logistic regression problem
Course contains a end-to-end DIY project to implement your learnings from the lectures
Graphically representing data in R before and after analysis
How to do basic statistical operations in R

People pursuing a career in data science
Working Professionals beginning their Data journey
Statisticians needing more practical experience

Questions & Answers

Add your question

Our advisors and other users will be able to reply to you

Who would you like to address this question to?

Fill in your details to get a reply

We will only publish your name and question

Emagister S.L. (data controller) will process your data to carry out promotional activities (via email and/or phone), publish reviews, or manage incidents. You can learn about your rights and manage your preferences in the privacy policy.

Reviews

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 6 years

Subjects

  • Global
  • Statistics
  • Teaching

Course programme

Introduction 1 lecture 03:10 Welcome to the course! Introduction 1 lecture 03:10 Welcome to the course! Welcome to the course! Welcome to the course! Welcome to the course! Welcome to the course! 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 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 Getting started with R and R studio 8 lectures 01:01:38 Installing R and R studio Basics of R and R studio Packages in R Inputting data part 1: Inbuilt datasets of R Inputting data part 2: Manual data entry Inputting data part 3: Importing from CSV or Text files Creating Barplots in R Creating Histograms in R Getting started with R and R studio 8 lectures 01:01:38 Installing R and R studio Basics of R and R studio Packages in R Inputting data part 1: Inbuilt datasets of R Inputting data part 2: Manual data entry Inputting data part 3: Importing from CSV or Text files Creating Barplots in R Creating Histograms in R Installing R and R studio Installing R and R studio Installing R and R studio Installing R and R studio Basics of R and R studio Basics of R and R studio Basics of R and R studio Basics of R and R studio Packages in R Packages in R Packages in R Packages in R Inputting data part 1: Inbuilt datasets of R Inputting data part 1: Inbuilt datasets of R Inputting data part 1: Inbuilt datasets of R Inputting data part 1: Inbuilt datasets of R Inputting data part 2: Manual data entry Inputting data part 2: Manual data entry Inputting data part 2: Manual data entry Inputting data part 2: Manual data entry Inputting data part 3: Importing from CSV or Text files Inputting data part 3: Importing from CSV or Text files Inputting data part 3: Importing from CSV or Text files Inputting data part 3: Importing from CSV or Text files Creating Barplots in R Creating Barplots in R Creating Barplots in R Creating Barplots in R Creating Histograms in R Creating Histograms in R Creating Histograms in R Creating Histograms in R Data Preprocessing 14 lectures 01:09:43 Gathering Business Knowledge Data Exploration The Data and the Data Dictionary Importing the dataset into R Univariate analysis and EDD EDD in R Outlier Treatment Outlier Treatment in R Missing Value Imputation Missing Value imputation in R Seasonality in Data Variable transformation in R Dummy variable creation: Handling qualitative data Dummy variable creation in R Data Preprocessing Training a Simple Logistic model in R Training a Simple Logistic model in R Training a Simple Logistic model in R Result of Simple Logistic Regression Result of Simple Logistic Regression Result of Simple Logistic Regression Result of Simple Logistic Regression Logistic with multiple predictors Logistic with multiple predictors Logistic with multiple predictors Logistic with multiple predictors Training multiple predictor Logistic model in R Training multiple predictor Logistic model in R Training multiple predictor Logistic model in R Training multiple predictor Logistic model in R Confusion Matrix Confusion Matrix Confusion Matrix Confusion Matrix Evaluating Model performance Evaluating Model performance Evaluating Model performance Evaluating Model performance Predicting probabilities, assigning classes and making Confusion Matrix Predicting probabilities, assigning classes and making Confusion Matrix Predicting probabilities, assigning classes and making Confusion Matrix Predicting probabilities, assigning classes and making Confusion Matrix Linear Discriminant Analysis Linear Discriminant Analysis Linear Discriminant Analysis Linear Discriminant Analysis Linear Discriminant Analysis in R Linear Discriminant Analysis in R Linear Discriminant Analysis in R Linear...

Additional information

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

See related categories

Machine Learning Basics: Classification models in R

£ 10 VAT inc.

The best Other Education courses

See all

See all