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所在平台: Udemy |
课程主页: https://www.udemy.com/course/artificial-intelligence-iii-in-java/
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课程名称：人工智能III - Java中的深度学习 课程概述：本课程旨在讲解深度学习的基础知识和卷积神经网络（CNN）。卷积神经网络是最成功的深度学习方法之一，自动驾驶汽车在很大程度上依赖于该算法。课程内容包括对密集连接神经网络及其问题的学习，随后进入卷积神经网络的理论及在Java中通过deeplearning4j库的实现。最后章节将探讨递归神经网络及其应用，包括自然语言处理和情感分析。 学习内容包括： 第一部分：多层神经网络和深度学习理论 - 激活函数（ReLU等） - 深度神经网络的实现 - 如何使用deeplearning4j（DL4J） 第二部分：卷积神经网络（CNN）的理论和实现 - 核心（特征检测器）概念 - 池化层和扁平化层 - 使用卷积神经网络进行光学字符识别（OCR） - 使用卷积神经网络进行微笑检测 - 从头开始创建表情符号检测应用 第三部分：递归神经网络（RNN）的理论 - 使用递归神经网络进行自然语言处理（NLP） - 使用递归神经网络进行情感分析 课程提供终身访问权限，包含40多个讲座！课后提供30天退款保证，若您对课程不满意，可以无条件退款。欢迎开始学习！
This course is about deep learning fundamentals and convolutional neural networks. Convolutional neural networks are one of the most successful deep learning approaches: self-driving cars rely heavily on this algorithm. First you will learn about densly connected neural networks and its problems. The next chapter are about convolutional neural networks: theory as well as implementation in Java with the deeplearning4j library. The last chapters are about recurrent neural networks and the applications - natural language processing and sentiment analysis!So you'll learn about the following topics:Section #1:multi-layer neural networks and deep learning theoryactivtion functions (ReLU and many more)deep neural networks implementationhow to use deeplearning4j (DL4J)Section #2:convolutional neural networks (CNNs) theory and implementationwhat are kernels (feature detectors)?pooling layers and flattening layersusing convolutional neural networks (CNNs) for optical character recognition (OCR)using convolutional neural networks (CNNs) for smile detectionemoji detector application from scratchSection #3:recurrent neural networks (RNNs) theoryusing recurrent neural netoworks (RNNs) for natural language processing (NLP)using recurrent neural networks (RNNs) for sentiment analysisThese are the topics we'll consider on a one by one basis.You will get lifetime access to over 40+ lectures!This course comes with a 30 day money back guarantee! If you are not satisfied in any way, you'll get your money back. Let's get started!
