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MATLAB深度学习简介
- 简单的介绍什么是深度学习、深度学习的应用场景等基础知识，帮助我们快速入门该领域(Briefly introduce what is the basic knowledge of deep learning, deep learning application scenarios, and help us quickly get started in this field.)
Deep learning_CNN DBN RBM
- 运用深度学习模型实现图像的分类，主要包括卷积神经网络CNN和深信度网络DBN(Classification of images using deep learning model includes convolutional neural network CNN and belief network DBN.)
Deep Learning
- Goodfellow、Bengio 和 Courville 三位大牛的《深度学习》中文版。 这本书首先讨论了机器学习的基础知识，从学术角度讲解了有效研究深度学习所需的应用数学（线性代数，概率和信息论等）知识；在此基础上，本书进一步讲解了深度学习算法和技术的相关知识；在最后一部分，《深度学习》这本书主要讲解了深度学习领域当前的研究趋势以及正在发生的变化。(Chinese versions of Deep Learning.)
deep-speed-constrained-ins-master
- 基于深度学习的约束捷联带的速度估计智能手机惯性导航(DEEP LEARNING BASED SPEED ESTIMATION FOR CONSTRAINING STRAPDOWN INERTIAL NAVIGATION ON SMARTPHONES)
图解深度学习（样章）
- Graphical deep learning (sample chapter)
tensorflow-vgg16-train-and-test-master
- vgg深度学习，图像识别，用于图像的分类，在python上运行(vgg deep learning, image recognition, used for image classification, running on Python)
5-3
- Tensorboard 网络运行-可视化网络参数-可视化调参(deep learning, Convolutional Neural Network)
TensorFlow
- 白化深度学习与Tensorfolw，很好的机器学习入门书籍。(White Deep Learning and Tensorfolw are good introductory books for machine learning.)
Deep Learning with Python
- 深度学习基本算法，深度学习with python作为标题建议介绍深度学习使用Python编程语言和开源Keras库，它允许简单快速的原型设计。 在Python深度学习中， 你将从一开始就学习深度学习，你将学习所有关于图像分类模型，如何使用深度学习获取文本和序列，甚至可以学习如何使用神经网络生成文本和图像。 本书是为那些具有Python技能的人员编写的，但你不必在机器学习，Tensorflow或Keras方面有过任何经验。你也不需要
Deep Neural Network
- 深度神经网络训练过程中：首先是进行初始化，根据需求设置神经网络的基本结构；然后进行前向传递（feedforward），层与层之间进行传递，求得误差；然后进行反向传播（back propogation），根据误差最小化原则，使用随机梯度下降法，对各个参数进行求导，确定下降方向，对各个参数进行更新(In the training process of deep neural network, firstly, initialization
deep-q-learning
- 深度强化學習代碼資料，Q學習的簡單實現。(Deep Q learning, simple codes implements)
雷达信号分选源码
- 用MATLAB深度学习进行雷达辐射源信号分选识别(Radar emitter signal sorting and recognition with MATLAB deep learning)
deep learning
- Bible of deep learning.
deep-learning
- Dynamic resource allocation dqn
TensorFlow for Deep Learning - 2018
- 机器学习 tensorflow，从入门到精通，案例实战(machin learn tensorflow)
Demo2_ImageClassifiction
- 使用Matlab深度学习工具箱-googlenet 图像分类(Using GoogLeNet to classify images using deep learning toolbox)
Speech watermarking using Deep Neural Networks
- Watermarking is a process in which both physical and digital media are marked using watermarks in order to protect ownership of the watermarked media. Digital water- marking is a technique where a watermark gets embed
Protecting the Intellectual Property of Deep Neural Networks with Watermarking: The Frequency Domain Approach
- Similar to other digital assets, deep neural network (DNN) models could suffer from piracy threat initiated by insider and/or outsider adversaries due to their inherent commercial value. DNN watermarking is a promisin
Darknet Master - Tor and Deep Web Secrets
- Book about Tor and Deep Web.
Deep Learning with Applications Using Python_ Chatbots and Face, Object, and Speech Recognition with Tensorflow and Kera
- Deep Learning with Applications Using Python_ Chatbots and Face, Object, and Speech Recognition with Tensorflow and Keras