搜索资源列表
neural-network
- 深度学习python实现，并附有MNIST上的测试程序，准确率98 以上-Deep learning learns low and high-level features large amounts of unlabeled data, improving classification on different, labeled, datasets. Deep learning can achieve an accuracy of 98 on the MNIST dataset.
Keras with Python
- 深度学习的新工具Keras包，使用Python程序设计语言实现。
TensorFlow实战_黄文坚（完整）
- 教会你如何通过Python语言实现TensorFlow框架，作为一个深度学习的初学者，想要接触TensorFlow框架的初学者，是非常好的学习资料。(Teach you how to implement TensorFlow framework through the Python language, depth of learning as a beginner, want to contact TensorFlow framework of beginners, is a very good
LSTM_learn-master
- 采用LSTM算法用python语言实现的信号时间序列预测，可预测信号的占用度(The LSTM algorithm is used to predict the signal time series in python language)
dbn
- 本程序是用python写的一个深度学习程序，该程序基于限制性玻尔兹曼机实现了深度信念网络。(This procedure is a deep learning program written in python, the program based on the limited Boltzmann machine to achieve a depth of faith network.)
新建文件夹 (2)
- 本程序是用python写的一个深度学习程序，该程序实现了卷积神经网络(This procedure is written in python with a deep learning program, the program achieved a convolution neural network)
deep-learning-with-python-notebooks-master
- Deep Learning With Python 原书配套代码。 包括所有常见的深度学习模型 注释丰富，代码规范 使用流行的keras库实现，jupyter notebook格式(Deep Learning With Python Original book matching code. Including all the common deep learning models Rich annotation, code specification Using the popula
Machine Learning Mastery with Python
- 各种机器学习算法的Python优雅实现，尤其是深度学习部分，应用到了TensorFlow(Python elegant implementation of various machine learning algorithms)
DeepLearning
- DeepLearning 工具包C, C++, Java, phython, scala代码集合,(DeepLearning Toolkit :C, C ++, Java, phython, scala code collection)
单层感知器
- 基于深度学习实现单层感知器的python代码，用单层感知器处理非线性分类问题,观察结果。(The Python code of single layer perceptron is realized based on depth learning, and the nonlinear classification problem is processed with a single layer perceptron, and the results are observed.)
Deep+Learning+with+Python+2017
- 如何使用python实现深度学习，是外文电子书籍，书里的内容较容易上手(How to use Python to realize deep learning)
DeepMind-Atari-Deep-Q-Learner-master
- 基于python环境的简明深度强化学习深度Q学习实现代码(Concise deep intensive learning based on Python environment and deep Q learning implementation code)
Object Detection
- 采用Python语言，在pycharm运行平台下，实现对特定图片中特定物体的检测与提取。(Python language is used to realize the detection and extraction of specific objects in specific pictures on the platform of pycharm.)
深度学习入门：基于Python的理论与实现.pdf+代码
- 本书是深度学习真正意义上的入门书，深入浅出地剖析了深度学习的原理和相关技术。书中使用Python3，尽量不依赖外部库或工具，从基本的数学知识出发，带领读者从零创建一个经典的深度学习网络，使读者在此过程中逐步理解深度学习。书中不仅介绍了深度学习和神经网络的概念、特征等基础知识，对误差反向传播法、卷积神经网络等也有深入讲解，此外还介绍了深度学习相关的实用技巧，自动驾驶、图像生成、强化学习等方面的应用，以及为什么加深层可以提高识别精度等“为什么”的问题。(This book is a true sen
【源代码】深度学习入门：基于Python的理论与实现
- 书籍《深度学习入门基于Python的理论与实现》源码(Book "deep learning entry based on Python theory and implementation" source code)
《深度学习入门：基于Python的理论与实现》
- 本书主要介绍深度学习的核心算法，以及在计算机视觉，语音识别、自然语言处理中的相关应用，适合深度学习从业人士或者相关研究生作为参考资料，也可以作为入门教程来大致了解深度学习的相关前沿技术(This book mainly introduces the core algorithms of deep learning, as well as relevant applications in computer vision, speech recognition and natural languag
pytorch-openpose-master
- 本例程是我研究生阶段做的一个小项目，该项目用pytorch的深度学习框架来进行人体姿态识别，能够实现头部和身体的骨架识别！图像处理方面加入了OpenCV包进行相关的处理，希望能帮助大家！(175/5000 This routine is a small project that I did in the graduate stage. The project uses pytorch's deep learning framework to recognize human body postu
深度（多层）极限学习机的python实现
- 深度极限学习机也叫多层极限学习机，ML-ELM。是黄广斌等人在极限学习机ELM基础上，将其拓展为深度学习的一种模式识别方法，原文文章：Representational learning with extreme learning machine for big data。(The deep extreme learning machine is also called the multi-layer extreme learning machine, ML-ELM. It is Huang Gu
xiangqi
- 象棋的人工实现，机器人下象棋，python实现智能象棋(chess Artificial realization of chess, robot chess, and intelligent chess by Python)
深度学习mtcnn
- 用市面上的摄像头，可以实现实时人脸识别功能。(The algorithm model of facenet face recognition is obtained through deep learning, and the backbone network of feature extraction is concept-resnetv1, which is developed from concept network and RESNET, with more channels and n