This is a recent analysis I conducted on economic bulletins from the ECB in pdf format. pdf2txt was used to convert into text format, the text was appropriately processed in Python, and then tf-idf was used to rank terms which were then incorporated into a word cloud. The intention behind this is to extract key terms from a document quickly, e.g. tariffs, downturn, debt, etc.

Would appreciate your opinions!

Link: Summarizing Economic Bulletin Documents with tf-idf

Hi everyone!

I am looking to get the book by Francois Chollet and I was just wondering if it is worth buying or not. Also, how detailed is it and what level does it start at?

I know the basics of deep learning and keras and I’d say that I can get things done in python comfortably. Would you recommend it for someone at this level?

Also I’m open to other suggestions. I’m looking for something that goes into a fair bit of detail on deep learning.

Thank you!

Hi, guys!

From now on, CVPR 2019 open access is accessible!

In addition to advanced metric learning research, many researches have been conducted on the real-world application such as person re-identification and image registration.

Through the following links, we can look at the work of CVPR 2019 in addition to the existing metric learning studies.

https://github.com/kdhht2334/Survey_of_Deep_Metric_Learning

Let’s say I have 3 features describing some value of 3 objects of importance. The 3 objects are identical.

In my current model, the three objects are basically randomly assigned to be the features object_0, object_1, object_2.

It doesn’t matter for the real life outcome which object is 0, 1 , or 2. Of course, the neural net will learn that these are interchangeable in theory, but is there a way people have been doing this in a more explicit way?
Would it improve training to, for example, always order the values from largest to smallest, 0-2? Or some manipulation like that?

If this is a terrible question or you have corrections about the way I asked it, feel free to let me know. I am still learning.

🙂

Thanks

Hi everyone. In case this is useful to anyone here, I wrote a BASH script for automated downloading of selected arXiv RSS feeds.

That content is parsed into two documents:

• keyword-matched articles of interest;
• the remaining articles.

The script can be scheduled to run daily via crontab, or manually executed.

By example, today among five arXiv RSS feeds my RSS reader provided 690 entries (including duplicated, cross-posted entries) while my script returned 344 de-duplicated (unique) articles.

• script: https://persagen.com/files/misc/arxiv-rss.sh
• accompanying research blog post: https://persagen.com/2019/06/10/arxiv-rss.html

https://arxiv.org/abs/1905.03970

I just started reading it and I wanted to get other people’s thoughts. Seems like it’s attempting to solve a pretty significant problem.