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所在平台: Coursera |
课程主页: https://www.coursera.org/learn/deep-neural-network
课程评论：没有评论
课程名称：改进深度神经网络：超参数调整、正则化与优化 课程概述：在深度学习专项课程的第二部分中，您将深入了解深度学习的“黑箱”过程，以系统地理解驱动性能和生成良好结果的机制。通过本课程的学习，您将掌握训练和开发测试集的最佳实践，分析偏差/方差以构建深度学习应用；能够使用初始化、L2正则化、dropout正则化、超参数调整、批量归一化和梯度检查等标准神经网络技术；实现并应用多种优化算法，例如小批量梯度下降、Momentum、RMSprop和Adam，并检查其收敛性；以及在TensorFlow中实现神经网络。 深度学习专项课程是我们基础性的项目，旨在帮助您理解深度学习的能力、挑战和影响，为参与尖端人工智能技术的发展做好准备。该课程为您提供了获得将机器学习应用于工作中的知识和技能的途径，提升您的技术职业生涯，并在人工智能领域迈出重要一步。 课程大纲： 第1部分：深度学习的实用方面 描述：探索和实验各种初始化方法，应用L2正则化和dropout以避免模型过拟合，然后应用梯度检查识别欺诈检测模型中的错误。 第2部分：优化算法 描述：通过添加更高级的优化、随机小批量处理和学习率衰减调度，开发您的深度学习工具箱，以加快模型训练。 第3部分：超参数调整、批量归一化和编程框架 描述：探索TensorFlow，一个能够快速轻松构建神经网络的深度学习框架，然后在TensorFlow数据集上训练神经网络。
Part: 1
Title:Practical Aspects of Deep Learning
Description:Discover and experiment with a variety of different initialization methods, apply L2 regularization and dropout to avoid model overfitting, then apply gradient checking to identify errors in a fraud detection model.
Part: 2
Title:Optimization Algorithms
Description:Develop your deep learning toolbox by adding more advanced optimizations, random minibatching, and learning rate decay scheduling to speed up your models.
Part: 3
Title:Hyperparameter Tuning, Batch Normalization and Programming Frameworks
Description:Explore TensorFlow, a deep learning framework that allows you to build neural networks quickly and easily, then train a neural network on a TensorFlow dataset.
In the second course of the Deep Learning Specialization, you will open the deep learning black box to understand the processes that drive performance and generate good results systematically. By the end, you will learn the best practices to train and develop test sets and analyze bias/variance for building deep learning applications; be able to use standard neural network techniques such as initialization, L2 and dropout regularization, hyperparameter tuning, batch normalization, and gradient checking; implement and apply a variety of optimization algorithms, such as mini-batch gradient descent, Momentum, RMSprop and Adam, and check for their convergence; and implement a neural network in TensorFlow. 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.
