Understanding Machine Learning

Understanding Machine Learning
MP4 | Video: h264, 1280×720 | Audio: AAC, 44100 Hz

This course provides introduction to how Machine Learning Models are created.

What you’ll learn
What are models in Machine Learning?
How to build models for Machine Learning?
How does Machine Learning build a Linear Regression model?

Requirements
Some knowledge of programming in any language is essential.
Description
Machine Learning is becoming ubiquitous across all industries. Already many applications have been identified which use Machine Learning now. Few examples include Spam Detection, Face Recognition, Emotion Analysis, Object Detection, Credit Card Fraud Detection, Weather Prediction, and the list is almost endless. More new applications are being identified by different industries almost everyday.

It is not just about applying superior technology for traditional problems when we apply Machine Learning. It is also about business sense since applying Machine Learning, we can make experiments and applications much more economical.

This course is a result of a discussion among my Project Team from our cohort in IIT, Kanpur learning Cyber Security. We have embarked to create a product for Malware Detection using Machine Learning. While all of us are getting grips on Malware Analysis, the team needed some inputs of Machine Learning. To fill the gap, I conducted some sessions with our Project Team members on Machine Learning. This course is a collection of the recording of these sessions.

Who this course is for:
Students
Professionals
Engineers
Researchers