001.005.010 NonVectorized Implementations of Conv2d and Pool2d

Описание: Welcome to the "Deep Learning CNN - Convolutional Neural Networks with Python" tutorial. In this video, we will be discussing how to build and optimize CNN models using the Python programming language. You will learn about the basics of deep learning, convolutional neural networks, and how to implement and optimize CNN models for image recognition.
This tutorial is suitable for those who have a basic understanding of Python programming and want to learn more about deep learning and CNN. We will provide examples of CNN implementation using Python libraries such as TensorFlow and Keras, as well as explain various techniques and strategies that can improve the performance of CNN models.
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Deep Learning CNN - Convolutional Neural Networks with Python

Chapter 5 Deep Neural Network Architecture
001. Convolution Revisited
002. Implementing Convolution in Python Revisited
003. Why Convolution
004. Filters Padding Strides
005. Padding Image
006. Pooling Tensors
007. CNN Example
008. Convolution and Pooling Details
009. MaxPooling Exercise
010. NonVectorized Implementations of Conv2d and Pool2d
011. Deep Neural Network Architecture Activity

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