The Convolutional Neural Network (CNN) has revolutionized computer vision tasks, achieving state-of-the-art results in object detection, image segmentation, and even generating photo-realistic images of non-existent subjects. This course is designed to equip you with the fundamentals of convolution and its relevance in deep learning, extending even to Natural Language Processing (NLP).Throughout the course, you'll delve into modern techniques like data augmentation and batch normalization while constructing contemporary architectures such as VGG. By the end, you'll fully grasp convolution, CNN architecture, and practical implementation using TensorFlow 2.What you'll learn:- Grasp the significance of convolution in Deep Learning- Comprehend and articulate the architecture of Convolutional Neural Networks (CNN)- Implement CNNs using TensorFlow 2- Apply CNNs to complex Image Recognition tasks- Apply CNNs to Natural Language Processing (NLP) for Text Classification, including tasks like Spam Detection and Sentiment AnalysisCourse Components:- Convolutional Neural Networks In Python Course.