Machine Learning for Engineering & Science Applications | IIT Madras - #49 Introduction to Convolution Neural Networks (CNN)
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.
Welcome to 'Machine Learning for Engineering & Science Applications' course !
This lecture introduces the concept of convolutional neural networks (CNNs), which are a type of neural network that is particularly well-suited for image recognition tasks. CNNs take images as input and learn to extract features from the images. The input to a CNN is typically a volume, which is a three-dimensional array of pixel values.
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
#CNN #ImageNet #VisualRecognitionChallenge #ImageParameterization #InputVector
Continue this lesson in the app
Install CourseHive on Android or iOS to keep learning while you move.