Linear Regression Analysis in Python - Machine Learning Basics
Linear Regression in Python. Simple and multiple Regression Analysis is essential for Machine Learning and Econometrics
Created by Abhishek and Pukhraj, Last Updated 27-Oct-2019, Language:English
You're looking for a complete Linear Regression course that teaches you everything you need to create a Linear Regression model in Python, 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 regression technique of Machine Learning.
Create a linear regression model in Python 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.
How this course will help you?
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
Why should you choose this course?
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.
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.
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 modelling to create predictive models and solve business problems.
What is Machine Learning?
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.
What is the Linear regression technique of Machine learning?
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.
Why learn Linear regression technique of Machine learning?
There are four reasons to learn Linear regression technique of Machine learning:
1. Linear Regression is the most popular machine learning technique
2. Linear Regression has fairly good prediction accuracy
3. Linear Regression is simple to implement and easy to interpret
4. It gives you a firm base to start learning other advanced techniques of Machine Learning
- Students will need to install Python and Anaconda software but we have a separate lecture to help you install the same
What Will I Get ?
- 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
Welcome to the course!Preview00:02:28
Setting up Python and Jupyter Notebook
Installing Python and AnacondaPreview00:03:04
Opening Jupyter NotebookPreview00:09:06
Introduction to JupyterPreview00:13:26
Basics of Statistics
Introduction to Machine Learning
Start-Tech Academy is a technology-based Analytics Education Company and aims at Bringing Together the analytics companies and interested Learners.
Our top quality training content along with internships and project opportunities helps students in launching their Analytics journey.
Founded by Abhishek Bansal and Pukhraj Parikh.
Working as a Project manager in an Analytics consulting firm, Pukhraj has multiple years of experience working on analytics tools and software. He is competent in MS office suites, Cloud computing, SQL, Tableau, SAS, Google analytics and Python.
Abhishek worked as an Acquisition Process owner in a leading telecom company before moving on to learning and teaching technologies like Machine Learning and Artificial Intelligence.