【课程四(Convolutional Neural Networks)，第二 周（Deep convolutional models: case studies） ——3.Programming assignments : Residual Networks】的更多相关文章

课程四(Convolutional Neural Networks)，第二 周（Deep convolutional models: case studies） ——3.Programming assignments : Residual Networks

Residual Networks Welcome to the second assignment of this week! You will learn how to build very deep convolutional networks, using Residual Networks (ResNets). In theory, very deep networks can represent very complex functions; but in practice, the…

[C4W2] Convolutional Neural Networks - Deep convolutional models: case studies

第二周 深度卷积网络:实例探究(Deep convolutional models: case studies) 为什么要进行实例探究?(Why look at case studies?) 这周我们首先来看看一些卷积神经网络的实例分析,为什么要看这些实例分析呢?上周我们讲了基本构建,比如卷积层.池化层以及全连接层这些组件.事实上,过去几年计算机视觉研究中的大量研究都集中在如何把这些基本构件组合起来,形成有效的卷积神经网络.最直观的方式之一就是去看一些案例,就像很多人通过看别人的代码来学习编程一…

课程四(Convolutional Neural Networks)，第二 周（Deep convolutional models: case studies） —— 0.Learning Goals

Learning Goals Understand multiple foundational papers of convolutional neural networks Analyze the dimensionality reduction of a volume in a very deep network Understand and Implement a Residual network Build a deep neural network using Keras Implem…

课程四(Convolutional Neural Networks)，第二 周（Deep convolutional models: case studies） —— 2.Programming assignments : Keras Tutorial - The Happy House (not graded)

Keras tutorial - the Happy House Welcome to the first assignment of week 2. In this assignment, you will: Learn to use Keras, a high-level neural networks API (programming framework), written in Python and capable of running on top of several lower-l…

课程四(Convolutional Neural Networks)，第二 周（Deep convolutional models: case studies） —— 1.Practice questions

[解释] 应该是same padding 而不是 valid padding . [解释] 卷积操作用的应该是adding additional layers to the network ,而是应该添加跳跃连接(Skip connection). [解释] 这一题感觉四个选项都是对的,但是提交答案的时候,显示答案有错误.欢迎留言讨论. ---------------------------------------------------------- 参考链接: 1.https://www.c…

[C6] Andrew Ng - Convolutional Neural Networks

About this Course This course will teach you how to build convolutional neural networks and apply it to image data. Thanks to deep learning, computer vision is working far better than just two years ago, and this is enabling numerous exciting applica…

课程四(Convolutional Neural Networks)，第四 周（Special applications: Face recognition & Neural style transfer） —— 2.Programming assignments：Art generation with Neural Style Transfer

Deep Learning & Art: Neural Style Transfer Welcome to the second assignment of this week. In this assignment, you will learn about Neural Style Transfer. This algorithm was created by Gatys et al. (2015) (https://arxiv.org/abs/1508.06576). In this as…

课程四(Convolutional Neural Networks)，第一周（Foundations of Convolutional Neural Networks） —— 3.Programming assignments：Convolutional Model: application

Convolutional Neural Networks: Application Welcome to Course 4's second assignment! In this notebook, you will: Implement helper functions that you will use when implementing a TensorFlow model Implement a fully functioning ConvNet using TensorFlow (…

课程四(Convolutional Neural Networks)，第一周（Foundations of Convolutional Neural Networks） —— 2.Programming assignments：Convolutional Model: step by step

Convolutional Neural Networks: Step by Step Welcome to Course 4's first assignment! In this assignment, you will implement convolutional (CONV) and pooling (POOL) layers in numpy, including both forward propagation and (optionally) backward propagati…

课程四(Convolutional Neural Networks)，第四 周（Special applications: Face recognition & Neural style transfer） —— 3.Programming assignments：Face Recognition for the Happy House

Face Recognition for the Happy House Welcome to the first assignment of week 4! Here you will build a face recognition system. Many of the ideas presented here are from FaceNet. In lecture, we also talked about DeepFace. Face recognition problems com…