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;微博:https://weibo.com/openingsource;电报群 https://t.me/OpeningSourceOrg

2018年9月3日:开源日报第179期

今日推荐开源项目:《真·快速爬虫·改 Photon》传送门:GitHub链接

推荐理由:顾名思义,这是个 python 爬虫,它可以帮你获取到目标网站上的链接,文件或者账户等等信息,然后分门别类的存起来。它最大的特点就是在工作时会使用其他的三个网站向目标发出请求,这不但提高了速度,还降低了断链接的风险。顺带一提,现在它已经开始支持使用插件了,尽管插件还正在开发,不过可以期待一下。


今日推荐英文原文:《9 Things You Should Know About TensorFlow》作者:Cassie Kozyrkov

原文链接:https://hackernoon.com/9-things-you-should-know-about-tensorflow-9cf0a05e4995

推荐理由:顾名思义,关于 TensorFlow 你需要知道的九件事情

9 Things You Should Know About TensorFlow

This morning I found myself summarizing my favorite bits from a talk that I enjoyed at Google Cloud Next in San Francisco, What’s New with TensorFlow?

Then I thought about it for a moment and couldn’t see a reason not to share my super-short summary with you (except maybe that you might not watch the video — you totally should check it out, the speaker is awesome) so here goes…

2018年9月3日:开源日报第179期

#1 It’s a powerful machine learning framework

TensorFlow is a machine learning framework that might be your new best friend if you have a lot of data and/or you’re after the state-of-the-art in AI: deep learning. Neural networks. Big ones. It’s not a data science Swiss Army Knife, it’s the industrial lathe… which means you can probably stop reading if all you want to do is put a regression line through 20-by-2 spreadsheet.

But if big is what you’re after, get excited. TensorFlow has been used to go hunting for new planets, prevent blindness by helping doctors screen for diabetic retinopathy, and help save forests by alerting authorities to signs of illegal deforestation activity. It’s what AlphaGo and Google Cloud Vision are built on top of and it’s yours to play with. TensorFlow is open source, you can download it for free and get started immediately.

2018年9月3日:开源日报第179期
Discovered with the help of TensorFlow, the planet Kepler-90i makes the Kepler-90 system the only other system we know of that has eight planets in orbit around a single star. No system has been found with more than eight planets, so I guess that means we’re tied with Kepler-90 for first place (for now). Learn more here.

#2 The bizarre approach is optional

I’m head over heels for TensorFlow Eager.

If you tried TensorFlow in the old days and ran away screaming because it forced you to code like an academic/alien instead of like a developer, come baaaack!

TensorFlow eager execution lets you interact with it like a pure Python programmer: all the immediacy of writing and debugging line-by-line instead of holding your breath while you build those huge graphs. I’m a recovering academic myself (and quite possibly an alien), but I’ve been in love with TF eager execution since it came out. So eager to please!

2018年9月3日:开源日报第179期

#3 You can build neural networks line-by-line

Keras + TensorFlow = easier neural network construction!

Keras is all about user-friendliness and easy prototyping, something old TensorFlow sorely craved more of. If you like object oriented thinking and you like building neural networks one layer at a time, you’ll love tf.keras. In just the few lines of code below, we’ve created a sequential neural network with the standard bells and whistles like dropout (remind me to wax lyrical about my metaphors for dropout sometime, they involve staplers and the flu).

2018年9月3日:开源日报第179期

Oh, you like puzzles, do you? Patience. Don’t think too much about staplers.

#4 It’s not only Python

Okay, you’ve been complaining about TensorFlow’s Python monomania for a while now. Good news! TensorFlow is not just for Pythonistas anymore. It now runs in many languages, from R to Swift to JavaScript.

2018年9月3日:开源日报第179期

#5 You can do everything in the browser

Speaking of JavaScript, you can train and execute models in the browser with TensorFlow.js. Go nerd out on the cool demos, I’ll still be here when you get back.

2018年9月3日:开源日报第179期
Real-time Human Pose Estimation in the browser with TensorFlow.js. Turn on your camera for a demo here. Or don’t get out of your chair. ¯\_(ツ)_/¯ Up to you.

#6 There’s a Lite version for tiny devices

Got a clunker desktop from a museum? Toaster? (Same thing?) TensorFlow Lite brings model execution to a variety of devices, including mobile and IoT, giving you more than a 3x boost in inference speedup over original TensorFlow. Yes, now you can get machine learning on your Raspberry Pi or your phone. In the talk, Laurence does a brave thing by live-demoing image classification on an Android emulator in front of thousands… and it works.

2018年9月3日:开源日报第179期
1.6 seconds to compute? Check! Banana with over 97% probability? Check! Toilet tissue? Well, I’ve been to a few countries where I suppose a sheet of paper like the one Laurence is holding up counts.

#7 Specialized hardware just got better

If you’re tired of waiting for your CPU to finish churning through your data to train your neural network, you can now get your hands on hardware specially designed for the job with Cloud TPUs. The T is for tensor. Just like TensorFlow… coincidence? I think not! A few weeks ago, Google announced version 3 TPUs in alpha.

2018年9月3日:开源日报第179期

#8 The new data pipelines are much improved

What’s that you’re doing with numpy over there? In case you wanted to do it in TensorFlow but then rage-quit, the tf.data namespace now makes your input processing in TensorFlow more expressive and efficient. tf.data gives you fast, flexible, and easy-to-use data pipelines synchronized with training.

2018年9月3日:开源日报第179期

#9 You don’t need to start from scratch

You know what’s not a fun way to get started with machine learning? A blank new page in your editor and no example code for miles. With TensorFlow Hub, you can engage in a more efficient version of the time-honored tradition of helping yourself to someone else’s code and calling it your own (otherwise known as professional software engineering).

2018年9月3日:开源日报第179期

TensorFlow Hub is a repository for reusable pre-trained machine learning model components, packaged for one-line reuse. Help yourself!

While we’re on the subject of community and not struggling alone, you might like to know that TensorFlow just got an official YouTube channel and blog.

That concludes my summary, so here’s the full talk to entertain you for the next 42 minutes.


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;微博:https://weibo.com/openingsource;电报群 https://t.me/OpeningSourceOrg