Summary on deep learning framework --- PyTorch  Updated on 2018-07-22 21:25:42  import osos.environ["CUDA_VISIBLE_DEVICES"]="4" 1. install the pytorch version 0.1.11  ## Version 0.1.11 ## python2.7 and cuda 8.0 sudo pip install http://…
 Summary on deep learning framework --- Theano && Lasagne 2017-03-23 1. theano.function output = input ** 2  f = theano.function([input], output) print(f(3)) >> the output is: 3^2 = 9. 2.  verbose = 1 or 0, does it have any difference ?   so…
 Summary on deep learning framework --- TensorFlow Updated on 2018-07-22 21:28:11 1. Check failed: s.ok() could not find cudnnCreate in cudnn DSO;  tensorflow/stream_executor/cuda/cuda_dnn.cc:221] Check failed: s.ok() could not find cudnnCreate in cu…
Summary on deep learning framework --- Torch7  2018-07-22 21:30:28 1. 尝试第一个 CNN 的 torch版本, 代码如下: -- We now have 5 steps left to do in training our first torch neural network -- 1. Load and normalize data -- 2. Define Neural Network -- 3. Define Loss…
Deep Learning framework --- MexNet 安装,测试,以及相关问题总结  一.安装:   参考博文:http://www.open-open.com/lib/view/open1448030000650.html  Note: gcc g++ 需要 4.8 版本. 二.…
Install and Compile MatConvNet: CNNs for MATLAB --- Deep Learning framework 2017-04-18  10:19:35 If you want to use matlab convnet, you just install according to the following tutorials: 1. Download and unzip the original source file from: http://www…
PyTorch Prerequisites - Syllabus for Neural Network Programming Series PyTorch先决条件 - 神经网络编程系列教学大纲 每个人都在发生什么事?欢迎来到PyTorch神经网络编程系列. 在这篇文章中,我们将看看做好最佳准备所需的先决条件. 我们将对该系列进行概述,并对我们将要开展的项目进行预览. 这将使我们对我们将要学习什么以及在系列结束时我们将拥有哪些技能有一个很好的了解. 不用多说,让我们直接了解细节. 此系列需要两个…
常用的deep learning frameworks 基本转自:http://www.codeceo.com/article/10-open-source-framework.html 1. Caffe 基于C++开发 2. Theano 大部分代码是使用CYthon开发的,主页有很详细的教程,在github上有Theano的软件包,另外还有一份pdf的tutorial 基于theano派生了许多的深度学习python软件包:Keras(documents).Lasagne(documents…
Tensor是一种特殊的数据结构,非常类似于数组和矩阵.在PyTorch中,我们使用tensor编码模型的输入和输出,以及模型的参数. Tensor类似于Numpy的数组,除了tensor可以在GPUs或其它特殊的硬件上运行以加速运算.如果熟悉ndarray,那么你也会熟悉Tensor API.如果不是,跟随此快速API上手. import torch import numpy as np Tensor 初始化 Tensor可以通过多种途径初始化.看看下面的例子: 直接从数据中初始化 Tenso…
torch.autograd 是PyTorch的自动微分引擎,用以推动神经网络训练.在本节,你将会对autograd如何帮助神经网络训练的概念有所理解. 背景 神经网络(NNs)是在输入数据上执行的嵌套函数的集合.这些函数由参数(权重.偏置)定义,并在PyTorch中保存于tensors中. 训练NN需要两个步骤: 前向传播:在前向传播中(forward prop),神经网络作出关于正确输出的最佳预测.它使输入数据经过每一个函数来作出预测. 反向传播:在反向传播中(backprop),神经网络根…
神经网络可以使用 torch.nn包构建. 现在你已经对autograd有所了解,nn依赖 autograd 定义模型并对其求微分.nn.Module 包括层,和一个返回 output 的方法 - forward(input). 例如,看看这个对数字图片进行分类的网络: convnet 这是一个简单的前馈网络.它接受输入,通过一层接一层,最后输出. 一个典型的神经网络训练过程如下: 定义神经网络,并包括一些可学习的参数(或权重) 通过输入数据集迭代 通过网络处理输入 计算损失(输出和真值的差距)…
你已经知道怎样定义神经网络,计算损失和更新网络权重.现在你可能会想, 那么,数据呢? 通常,当你需要解决有关图像.文本或音频数据的问题,你可以使用python标准库加载数据并转换为numpy array.然后将其转换为 torch.Tensor. 对于图像,例如Pillow,OpenCV 对于音频,例如scipy和librosa 对于文本,原生Python或基于Cython的加载,或NLTK和SpaCy 针对视觉领域,我们创建了一个名为 torchvision 的包,拥有用于ImageNet.C…
百度云链接: 链接:https://pan.baidu.com/s/1xU-CxXGCvV6o5Sksryj3fA 提取码:gawn…
Tensors 1. construst matrix 2. addition 3. slice from __future__ import print_function import torch # construst a 5*3 matrix. # method 1 # x = torch.LongTensor(5, 3) x = torch.FloatTensor(5, 3) print(x) # method 2 x = torch.randn(5, 3) print(x) # get…
What's the most effective way to get started with deep learning?       29 Answers     Yoshua Bengio, My lab has been one of the three that started the deep learning approach, back in 2006, along with Hinton's... Answered Jan 20, 2016   Originally Ans…
深度学习软件 -CPU vs GPU -Deep Learning Framework - Caffe / Caffe2 - Theano / TensorFlow - Torch / PyTorch -CPU vs GPU(并行计算) -cuBLAS:Matrix Multiplication and so on.(BLAS:Basic Linear Algebra Subprograms) -cuFFT:快速傅里叶变换. -cuDNN:cu深度神经网络. 图1 CPU与GPU设计结构对比(为…
最近在学深度学习相关的东西,在网上搜集到了一些不错的资料,现在汇总一下: Free Online Books  by Yoshua Bengio, Ian Goodfellow and Aaron Courville Neural Networks and Deep Learning42 by Michael Nielsen Deep Learning27 by Microsoft Research Deep Learning Tutorial23 by LISA lab, University…
转自:http://www.jeremydjacksonphd.com/category/deep-learning/ Deep Learning Resources Posted on May 13, 2015   Videos Deep Learning and Neural Networks with Kevin Duh: course page NY Course by Yann LeCun: 2014 version, 2015 version NIPS 2015 Deep Learn…
Awesome Deep Learning  Table of Contents Free Online Books Courses Videos and Lectures Papers Tutorials Researchers WebSites Datasets Frameworks Miscellaneous Contributing Free Online Books Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Cou…
Deep Learning in a Nutshell: History and Training This series of blog posts aims to provide an intuitive and gentle introduction to deep learning that does not rely heavily on math or theoretical constructs. The first part in this series provided an…
Top Deep Learning Projects A list of popular github projects related to deep learning (ranked by stars). Last Update: 2016.08.09 Project Name Stars Description TensorFlow 29622              Computation using data flow graphs for scalable machine lear…
1.结构图 Introduction Feature extraction, deformation handling, occlusion handling, and classification are four important components in pedestrian detection. Existing methods learn or design these components either individually or sequentially. The inte…
Deep Learning in a Nutshell: Core Concepts This post is the first in a series I’ll be writing for Parallel Forall that aims to provide an intuitive and gentle introduction todeep learning. It covers the most important deep learning concepts and aims…
Deep Learning in a Nutshell: Core Concepts Share:   Posted on November 3, 2015by Tim Dettmers 7 CommentsTagged cuDNN, Deep Learning, Deep Neural Networks, Machine Learning,Neural Networks   This post is the first in a series I’ll be writing for Paral…
Machine and Deep Learning with Python Education Tutorials and courses Supervised learning superstitions cheat sheet Introduction to Deep Learning with Python How to implement a neural network How to build and run your first deep learning network Neur…
转自:机器学习(Machine Learning)&深度学习(Deep Learning)资料 <Brief History of Machine Learning> 介绍:这是一篇介绍机器学习历史的文章,介绍很全面,从感知机.神经网络.决策树.SVM.Adaboost到随机森林.Deep Learning. <Deep Learning in Neural Networks: An Overview> 介绍:这是瑞士人工智能实验室Jurgen Schmidhuber写的最…
Decision Boundaries for Deep Learning and other Machine Learning classifiers H2O, one of the leading deep learning framework in python, is now available in R. We will show how to get started with H2O, its working, plotting of decision boundaries and…
Displaying 1-16 of 86 results for: deep learning Deep Learning By Adam Gibson, Josh Patterson Publisher: O'Reilly Media Release Date: September 2015   Deep Learning By O'Reilly Media, Inc. Publisher: O'Reilly Media Release Date: June 16, 2015   Funda…
边缘智能:按需深度学习模型和设备边缘协同的共同推理 本文为SIGCOMM 2018 Workshop (Mobile Edge Communications, MECOMM)论文. 笔者翻译了该论文.由于时间仓促,且笔者英文能力有限,错误之处在所难免:欢迎读者批评指正. 本文及翻译版本仅用于学习使用.如果有任何不当,请联系笔者删除. 本文作者包含3位,En Li, Zhi Zhou, and Xu Chen@School of Data and Computer Science, Sun Yat…
https://blog.csdn.net/starzhou/article/details/78845931 The Wide and Deep Learning Model(译文+Tensorlfow源码解析) 原创 2017年11月03日 22:14:47 标签: 深度学习 / 谷歌 / tensorflow / 推荐系统 / 397 编辑 删除 Author: DivinerShi 本文主要讲解Google的Wide and Deep Learning 模型.本文先从原始论文开始,先一步…