TPU, Listing Embeddings, Pyception
Weekly Reading List #2
Issue #2: 2018/04/23 to 2018/04/29
This is an experimental series in which I briefly introduce the interesting data science stuffs I read, watched, or listened to during the week. Please give this post some claps if you’d like this series to be continued.
Hands-on with the Google TPUv2
It’s been a while since Google made TPU available on their cloud platform in beta in February. I’m curious if there are already some people sharing their experience using TPU on the Internet. So I did some Googling…
Google's Tensor Procesing Unit (TPU) has been making a splash in the ML/AI community for a lot of good reasons…blog.paperspace.com
The article above then led me to…
UPDATE: Thanks for all your ideas on improving the benchmark! We are currently collecting all feedback and already…blog.riseml.com
So it seems the released TPU (TPUv2) is a bit more cost effective then . However, the fact that TPU supports only mixed precision training may become an issue sometimes.
The downside is that there are a lot of hoops to jump through to be able to use TPU, according to the Paperspace blog post. And some of them are quite intimidating. Also, only Tensorflow supports TPU so far.
Update on 2018/4/26
Google recently added the Tensor Processing Unit v2 (TPUv2), a custom-developed microchip to accelerate deep learning…blog.riseml.com
This new post by RiseML showed that TPU might be even more cost-effective than we thought, and the top-1 accuracy (on the validation set) is bit better coming from TPU than from GPU.
Airbnb Listing Embeddings
This post by Airbnb describes how they embeds every listing on their platform to improve similar listing recommendations and later real-time search personalization. Its is well-written and easy to read. The model evaluation parts are particularly interesting. The methodology should be applicable to other similarity problems, too.
Authors: Mihajlo Grbovic, Haibin Cheng, Qing Zhang, Lynn Yang, Phillippe Siclait and Matt Jonesmedium.com
A freaking hilarious and surprisingly educational parody by Anaconda.
A Nice Telegram Channel about Data Science
(I’m not affiliated with the channel.) I’ve found the links posted in this channel relevant and informative: