Last Updated on December 21, 2023 by GeeksGod
Course : Linear Regression and Logistic Regression using R Studio
Free Udemy Coupon, R Studio Regression – Complete Linear and Logistic Regression Course
You’re looking for a complete Linear Regression and Logistic Regression course that teaches you everything you need to create a Linear or Logistic Regression model in R Studio, right?
You’ve found the right Linear Regression course!
After completing this course you will be able to:
- Identify the business problem which can be solved using linear and logistic regression technique of Machine Learning.
- Create a linear regression and logistic regression model in R Studio and analyze its result.
- Confidently practice, discuss, and understand Machine Learning concepts.
A Verifiable Certificate of Completion is presented to all students who undertake this Machine learning basics course.
Why Choose This 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 technique of machine learning, which is Linear Regression.
This course covers all the steps that one should take while solving a business problem through linear regression.
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.
We are also the creators of some of the most popular online courses – with over 150,000 enrollments and thousands of 5-star reviews like these ones:
- This is very good, i love the fact the all explanation given can be understood by a layman – Joshua
- Thank you Author for this wonderful course. You are the best and this course is worth any price. – Daisy
Our Promise
Teaching our students is our job and we are committed to it. If you have any questions about the course content, practice sheet or anything related to any topic, you can always post a question in the course or send us a direct message.
Download Practice files, take Quizzes, and complete Assignments
With each lecture, there are class notes attached for you to follow along. You can also take quizzes to check your understanding of concepts. Each section contains a practice assignment for you to practically implement your learning.
What is covered in this course?
This course teaches you all the steps of creating a Linear Regression model, which is the most popular Machine Learning model, to solve business problems.
Below are the course contents of this course on Linear Regression:
- Section 1 – Basics of Statistics
- Types of data
- Types of statistics
- Graphical representations to describe the data
- Measures of center like mean, median, and mode
- Measures of dispersion like range and standard deviation
- Section 2 – Python basics
- Setting up the python and Jupyter environment
- Performing basic operations in Python
- Understanding the importance of different libraries such as Numpy, Pandas & Seaborn
- Section 3 – Introduction to Machine Learning
- What does Machine Learning mean
- Meanings of different terms associated with machine learning
- Examples to understand machine learning
- Steps involved in building a machine learning model
- Section 4 – Data Preprocessing
- Actions to get the data and prepare it for analysis
- Understanding the importance of business knowledge
- Data exploration
- Uni-variate analysis and bi-variate analysis
- Outlier treatment
- Missing value imputation
- Variable transformation and correlation
- Section 5 – Regression Model
- Simple linear regression
- Multiple linear regression
- Quantifying models accuracy
- Meaning of F statistic
- Interpretation of categorical variables in the results
- Variations to the ordinary least squared method
- Interpreting the result to find out the answer to a business problem
By the end of this course, your confidence in creating a regression model in Python will soar. You’ll have a thorough understanding of how to use regression modeling to create predictive models and solve business problems.
Go ahead and click the enroll button, and I’ll see you in lesson 1!
Cheers
Start-Tech Academy
FAQs about Machine Learning
Below is a list of popular FAQs of students who want to start their Machine learning journey:
- What is Machine Learning?
- What is the Linear regression technique of Machine learning?
- Why learn Linear regression technique of Machine learning?
- Linear Regression is the most popular machine learning technique
- Linear Regression has fairly good prediction accuracy
- Linear Regression is simple to implement and easy to interpret
- It gives you a firm base to start learning other advanced techniques of Machine Learning
- How much time does it take to learn Linear regression technique of machine learning?
- What are the steps I should follow to be able to build a Machine Learning model?
Machine Learning is a field of computer science which gives the computer the ability to learn without being explicitly programmed. It is a branch of artificial intelligence based on the idea that systems can learn from data, identify patterns and make decisions with minimal human intervention.
Linear Regression is a simple machine learning model for regression problems, i.e., when the target variable is a real value.
Linear regression is a linear model, e.g. a model that assumes a linear relationship between the input variables (x) and the single output variable (y). More specifically, that y can be calculated from a linear combination of the input variables (x).
When there is a single input variable (x), the method is referred to as simple linear regression.
When there are multiple input variables, the method is known as multiple linear regression.
There are four reasons to learn Linear regression technique of Machine learning:
Linear Regression is easy but no one can determine the learning time it takes. It totally depends on you. The method we adopted to help you learn Linear regression starts from the basics and takes you to an advanced level within hours. You can follow the same, but remember you can learn nothing without practicing it. Practice is the only way to remember whatever you have learned. Therefore, we have also provided you with another data set to work on as a separate project of Linear regression.
