Hand Written Digit Classification with CNN
STEPS INVOLVED
1.Import the libraries (tf and keras) and load the dataset (mnist contains 60,000 training images •10,000 testing images)
2.Reshaping and Normalizing the Images (preprocessing - grayscaling for kerasAPI(0 to 255))
3.Building the Convolutional Neural Network (sequential model : convo2d, maxpool, flatten, dropout, dense)
4.Compiling and training the model ( adam optimizer, sparse categorical cassentropy with relu and softmax)
5.Evaluating the Model
read the blog for a detailed explanation by me hand_written_digit_detection