#10 Bayes' Theorem | Simple Examples | Machine Learning for Engineering & Science Applications

Machine Learning for Engineering & Science Applications | IIT Madras - #10 Bayes' Theorem | Simple Examples | Machine Learning for Engineering & Science Applications

Unlock the Future: Master AI & Machine Learning with NPTEL-IITM’s Comprehensive Course! Dive into Neural Networks, Deep Learning, Probabilities, and Optimization Techniques tailored for Engineering & Science Applications. Your AI journey starts here!

4.0 (2)

22 learners

What you'll learn

Understand the historical development and foundational concepts of artificial intelligence.
Gain proficiency in applying machine learning techniques to engineering and science problems.
Develop skills in using linear algebra and calculus for machine learning modeling.
Learn to implement and optimize machine learning algorithms using Python packages.

This course includes

32 hours of video
Certificate of completion
Access on mobile and TV

Summary

Keywords

Lecture 10 12 20 12 18 Machine Learning for Engineering and Science Applications Prof. Ganapathy Prof.Balaji Srinivasan Online Course Video Lecture NPTEL

Full Transcript

Welcome to 'Machine Learning for Engineering & Science Applications' course ! This lecture focuses on conditional probability, a fundamental concept in probability theory. It explores how to calculate conditional probabilities using joint probability tables. The lecture uses an example involving a basket containing fruits to illustrate the concepts. NPTEL Courses permit certifications that can be used for Course Credits in Indian Universities as per the UGC and AICTE notifications. To understand various certification options for this course, please visit https://nptel.ac.in/courses/106106198 #ConditionalProbability #JointProbability #ProbabilityTable

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