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今日推荐开源项目:《TensorFlow深度学习模型

推荐理由:关心深度学习的同学,这里有一串官方整理好的深度学习模型,该存储库包含许多在TensorFlow中实现的不同模型,GitHub 地址是 https://github.com/tensorflow/models

官方模型

mnist:对来自MNIST数据集的数字进行分类的基本模型。最开始设计出来的目的是用于识别数字,同时也是深度学习的一个样例。

 

resnet:一个深度残差网络,可用于CIFAR-10和ImageNet的1000个类别的数据集进行分类。由于深度学习模型的练习次数达到某一个值时识别准确率以及识别性能会下降,因而开发出了可以提高学习深度的网络。

 

wide_deep:将广泛的模型和深度网络相结合的模型,用于对人口普查收入数据进行分类。经过学习后,神经网络可以通过其中几个数据的值推断出其他数据的值。

 

研究模型(非官方模型,个人使用)

adversarial_crypto:保护与对抗式神经密码学的通信。

adversarial_text:具有对抗训练的半监督序列学习。

attention_ocr:图像识别文本提取模型(用于高干扰的现实场景)。

autoencoder:各种自动编码器。

brain_coder:带强化学习的程序综合器。

cognitive_mapping_and_planning:为视觉导航实现基于空间记忆的映射和规划体系结构。

compression:使用预先训练的剩余GRU网络压缩和解压缩图像。

deeplab:用于语义图像分割的深度标签。

delf:用于匹配和检索图像的深层局部特征。

differential_privacy:来自多位教师的学生隐私保护模型。

domain_adaptation:域分离网络。

gan:生成对抗式网络。

im2txt:用于转换图像字幕为文本的神经网络。

inception:用于计算机视觉的深度卷积网络。

learning_to_remember_rare_events:用于深度学习的大型终身记忆模块。

lfads:用于分析神经科学数据的顺序变分自动编码器。

lm_1b:以十亿单词为基准测试的语言建模。

maskgan:用GAN生成文本。

namignizer:识别并生成名称。

neural_gpu:高度并行的神经计算机。

neural_programmer:用逻辑和数学运算增强的神经网络。

next_frame_prediction:通过交叉卷积网络进行概率性的下一帧合成。

object_detection:定位和识别单个图像中的多个对象。

pcl_rl:用于几种强化学习算法的代码,包括路径一致性学习。

ptn:用于三维物体重建的透视变换网。

qa_kg:模块网络,用于在知识图上进行问题解答。

real_nvp:使用实值非容量保留(真实NVP)变换的密度估计。

rebar:离散潜变量模型的低方差,无偏差梯度估计。

resnet:深层和广泛的残余网络。

skip_thoughts:递归神经网络句 – 矢量编码器。

slim:TF-Slim中的图像分类模型。

street:使用深度学习从图像中识别街道的名称(仅限于法国)。

swivel:用于生成复合词的Swivel算法。

syntaxnet:自然语言语法的神经模型。

tcn:从多视点视频学习的自我监督表示。

textsum:序列到序列与文本摘要的关注模型。

transformer:空间转译网络,可以对网络内的数据进行空间处理。

video_prediction:用神经平流预测未来的视频帧(类似于next_frame_prediction)。

关于其中的几个项目:

Mnist实际上是一个简单的视觉计算数据集,目的大概就是为用机器学习练习对数据进行处理。它本身可能没有非常有用的一个应用,只是学习机器学习的‘陪练’。Mnist主要用来训练图像识别相关的机器学习模块

https://github.com/zalandoresearch/fashion-mnist

这里有一个很有名也很有趣的mnist数据集fashion-mnist,由60,000个示例的训练集和10,000个示例的测试集组成。每个示例都是28×28灰度图像,与10个类别的标签相关联。(T恤/上衣,裤子,套头衫,连衣裙,大衣,凉鞋,衬衫,运动鞋,包,脚踝靴),作者制作这个数据集的本意是用作验证mnist算法的基准。

 

wide_deep给的则是用人口普查收入数据预测收入,正如其名字所说的,这是一个深宽模型。也基本是用来验证tensorflow对深宽模型处理的应用。

 

此外,介绍两个难度较低的tensorflow的项目:

验证码识别:

http://blog.csdn.net/sushiqian/article/details/78305340

验证码识别的原理与对mnist手写数字数据集的处理有异曲同工之妙,也是新手练习的选择之一

 

五子棋:

https://github.com/junxiaosong/AlphaZero_Gomoku

这个五子棋项目模仿alphago做成的项目,十分有趣,对alphago有兴趣的可以了解下


今日推荐英文原文:《Happy 25th birthday Red Hat Linux!》作者: Steven J. Vaughan-Nichols

原文链接:https://www.zdnet.com/article/happy-25th-birthday-red-hat-linux/

推荐理由:今天, Linux 在我们身边随处可见,不过,25年前呢,可不是这样,红帽在开源历史上有着非常重要的地位,也是迄今为止商业化最成功的开源领域公司,现在,它25岁了。

Happy 25th birthday Red Hat Linux!

oday, Linux and open-source software rule the tech world. Twenty-five years ago? It was an amateur operating system that only geeks knew about. One of the main reasons Linux got from there to here is Red Hat turned a hobby into an IT force.

Red Hat co-founder Bob Young — who had run a rental typewriter business — became interested in Linux. In 1993, he founded ACC Corporation, a catalog business that sold Slackware Linux CDs and open-source software.

Everyone knew, as Young remembered later, “Solaris was much better than Linux, but it was only by using Linux that he could tweak the operating systems to meet their needs.” Young realized that while he couldn’t sell Linux as being better, faster, or having more features than Unix in those days, he could sell one benefit: users could tune it to meet their needs. That would prove to be a key selling point, as it still is today.

So, he joined forces with Linux developer Marc Ewing, and from Young’s wife sewing closet, they launched Red Hat Linux. Like other early Linux businesses, Red Hat started out by selling diskettes, then servers, services, and CDs.

Today, in an interview, Young said, “What I love about the story is that it took many great contributors from the free software/open-source communities including Stallman to Torvalds. To Marc and I and our team-mates to Matthew Szulik, and now Jim and his vast team. None of us could have fundamentally changed the way software is developed and deployed without all the others.”

Young continued, “As my internet software developer son-in-law puts it: he and his colleagues couldn’t do what they do without all the free and open software that Red Hat is both a contributor to and a beneficiary from.” He concluded, “And then there is our families. I would not have been able to make my contribution if my wife Nancy had not been willing to bet our kids’ college education on building a software business on a model never done before.”

First though, Red Hat had to find the magic formula, which would bring it success while so many other of its contemporaries, such as Calera, TurboLinux, and Mandrake, were left in history’s ashbin.

Red Hat’s current CEO Jim Whitehurst told me in an interview, “The real contribution we’ve made, besides open-source software, has been the enterprise business model. It’s obvious now, but it wasn’t obvious at the time.”

I would say so!

In 2003, Paul Cormier, then Red Hat’s vice president of engineering and now Red Hat’s president of Products and Technologies, led the way to leaving behind its early inexpensive distribution, Red Hat Linux, to move to a full business Linux: Red Hat Enterprise Linux (RHEL).

Cormier said later that many “engineers at the time didn’t care about a business model. They wanted to work on Red Hat Linux. We had some level of turmoil inside the company with going to this new model. Some engineers left, but more stayed.”

Many users didn’t like it one darn bit either. They saw Red Hat as abandoning its first customers. Enterprise customers saw it differently.

Whitehurst, who took Red Hat’s reins in 2008, said, “Once RHEL was in the market we had to support it full stop to made it truly consumable for the enterprise.” They did so and the rest is history.

Red Hat grew and grew. In its latest quarter, Red Hat realized $772 million of revenue, which was up 23 percent year over year. Not bad for a company built around an operating system that people back in the day thought of as being only for the lunatic fringe.

Today, Whitehurst, remarked, “Linux is the default choice for open-source companies and enterprises. Ten years ago people still had doubts about open source. Now it’s the default choice for clouds, AI, and big data.” Indeed, “Are there even any important big data or AI projects that aren’t build on open source?” he asked.

The answer, by the by, is no.

It’s not just Red Hat, it’s all of Linux and open-source. “At a Red Hat development site,” Whitehurst said, “an engineer asked me about Microsoft competing with open source.” Whitehurst replied: “Microsoft is not the issue, Windows is a competitor to Linux and we’d love to kill it, but the largest enterprise software company in the world is pro-open source and that’s good for all of us.”

While Red Hat makes the bulk of its money from Linux, Red Hat is no longer just a Linux company. Its eyes are now set on the cloud. Red Hat is determined to use OpenStack to gain a place as big in clouds as the role it already has in Linux.

Red Hat realizes it’s not just the cloud. The company is also heavily invested in containers and container management. Nothing shows that more than its recent acquistion of CoreOS, a leading Kubernetes company.

Linux brought Red Hat where it is today. Moving towards tomorrow it will use open-source software to use the cloud, containers, and container orchestration to rise even further in its next 25 years.


每天推荐一个 GitHub 优质开源项目和一篇精选英文科技或编程文章原文,欢迎关注开源日报。交流QQ群:202790710;电报群 https://t.me/OpeningSourceOrg