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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/neural-networks-deep-learning
课程评论：没有评论
课程名称: 神经网络与深度学习 概述: 在深度学习专项课程的第一门课程中，您将学习神经网络和深度学习的基础概念。到课程结束时，您将熟悉推动深度学习崛起的重要技术趋势；能够构建、训练和应用全连接的深度神经网络；实现高效的向量化神经网络；识别神经网络架构中的关键参数；并将深度学习应用于自己的项目。 深度学习专项课程是我们基础培训项目，旨在帮助您理解深度学习的能力、挑战和后果，为您参与前沿人工智能技术的发展做好准备。它为您提供了获得应用机器学习所需知识和技能的途径，以提升您的技术职业生涯，并在人工智能领域迈出决定性的一步。 课程大纲: 第一部分: 深度学习简介 描述: 分析推动深度学习崛起的主要趋势，并举例说明其在当今的应用场景。 第二部分: 神经网络基础 描述: 以神经网络的思维方式设置机器学习问题，并利用向量化加速模型。 第三部分: 浅层神经网络 描述: 构建一个具有一个隐藏层的神经网络，使用前向传播和反向传播。 第四部分: 深层神经网络 描述: 分析深度学习的关键计算，然后利用这些知识构建和训练深度神经网络以解决计算机视觉任务。
Part: 1
Title:Introduction to Deep Learning
Description:Analyze the major trends driving the rise of deep learning, and give examples of where and how it is applied today.
Part: 2
Title:Neural Networks Basics
Description:Set up a machine learning problem with a neural network mindset and use vectorization to speed up your models.
Part: 3
Title:Shallow Neural Networks
Description:Build a neural network with one hidden layer, using forward propagation and backpropagation.
Part: 4
Title:Deep Neural Networks
Description:Analyze the key computations underlying deep learning, then use them to build and train deep neural networks for computer vision tasks.
In the first course of the Deep Learning Specialization, you will study the foundational concept of neural networks and deep learning. By the end, you will be familiar with the significant technological trends driving the rise of deep learning; build, train, and apply fully connected deep neural networks; implement efficient (vectorized) neural networks; identify key parameters in a neural network’s architecture; and apply deep learning to your own applications. The Deep Learning Specialization is our foundational program that will help you understand the capabilities, challenges, and consequences of deep learning and prepare you to participate in the development of leading-edge AI technology. It provides a pathway for you to gain the knowledge and skills to apply machine learning to your work, level up your technical career, and take the definitive step in the world of AI.
