Implemented a Convolutional Neural Network for CAPTCHA Recognition. The training was done for 500 epochs with a batch size of 32, with Adam optimizer and Categorical Cross-Entropy as the loss function. The model was able to correctly predict the Captcha text for 210 images out of the total 214 test images. The accuracy of the model is 98.13%.
