Great Learning
FSL
Machine Learning

Machine Learning Pipeline

Take free Machine Learning Pipeline course & learn to solve real world problems in various domains.

Instructor:

Dr. Sunil Kumar

4.52

Ratings

Intermediate

Level

3.0 Hrs

Learning hours

3.4K+

Learners

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Machine Learning Pipeline

Provided by

Foundation Skills Library

Skills you’ll Learn

Introduction to Machine Learning

Understanding the ML Pipeline

Data Preparation

Formatting Data

Data Transformation

Building ML models

About this Course

Machine learning is one of these domains that is aiming to solve problems in almost all of the other domains out there. The applications of Machine Learning are nearly endless as is and the list just keeps growing. Since the domain is trending with regards to how easy it is able to solve multiple problems, it becomes key that you as a learner are aware of how best you can put these algorithms to use and solve real-world problems. Keeping exactly this in mind, we here at Great Learning have come up with this course helping you understand the Machine Learning pipeline in detail and further reinforce the concepts of how you could use it to solve real-world problems in multiple domains.

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Course Outline

Introduction to Machine Learning and Linear Regression

Data is the soul of Machine Learning, and there are specific methods to deal with it efficiently. This module first introduces Machine Learning and talks about the mathematical procedures involved. You will learn about supervised and unsupervised learning, Data Science Machine Learning steps, linear regression, Pearson's coefficient, best fit line, and coefficient of determinant. Lastly, you will be going through a case study to help you effectively comprehend Machine Learning concepts.

Introduction on Machine Learning Pipeline

Data Preparation

Formatting Data

Data Transformation

Our course instructor

Dr. Sunil Kumar

GM - Engineering Innovation

3.4K+ Learners

1 Courses

Dr Sunil has a PhD in computer science (specializing in machine learning and natural language processing). He is an AI researcher with 15+ years of industry experience. Prior to joining one of the world's renowned logistics firm. He was with the AI Center of Excellence.
He has published several research papers in Scopus, IEEE journals and is a regular speaker at various meet-ups. He also has a book published this year by Packt publishers, UK called 'R Machine Learning Projects'. He is an avid coder and has won multiple hackathons in his spare time.