Machine Learning for Engineering & Science Applications | IIT Madras - #56 Train Network for Image Classification | Machine Learning for Engineering & Science Applications

Welcome to 'Machine Learning for Engineering & Science Applications' course ! This lecture discusses how to code a CNN in MATLAB. The example script provided by MATLAB shows how to create a CNN architecture for MNIST digit classification. The ImageDatastore function can be used to load the data and store the labels. The splitEachLabel function can be used to split the data into training, validation, and testing sets. The trainingOptions function can be used to set the parameters for training the network. The trainNetwork function can be used to train the network. 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 #MATLAB #MNIST #DigitClassification #ImageDatastore #DeepLearningToolbox #TrainingOptions #StochasticGradientDescent