Softpedia: OpenSSH 7.4 addresses many of the security issues discovered since OpenSSH 7.3.

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As you might have heard already, Firebug has been discontinued as a separate Firefox add-on.
The reason for this huge change is Electrolysis, Mozilla’s project name for a redesign of Firefox architecture to improve responsiveness, stability, and security. Electrolysis’s multiprocess architecture makes it possible for Firefox to run its user interface (things like the address bar, the tabs and menus) in one process while the content (websites) runs in other processes. With multiprocess architecture, if a website crashes, it doesn’t also crash the whole browser.
Unfortunately, Firebug wasn’t designed with multiprocess in mind, and making it work in this new scenario would have required an extremely difficult and costly rewrite. The Firebug Working Group agreed they didn’t have enough resources to implement such a massive architectural change. Additionally, Firefox’s built-in developer tools have been gaining speed, so it made sense to base the next version of Firebug on these tools instead.
The decision

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When I was first introduced to Long Short-Term Memory networks (LSTMs), it was hard to look past their complexity. I didn’t understand why they were designed they way they were designed, just that they worked. It turns out that LSTMs can be understood, and that, despite their superficial complexity, LSTMs are actually based on a couple incredibly simple, even beautiful, insights into neural networks. This post is what I wish I had when first learning about recurrent neural networks (RNNs).
In this post, we do a few things:
We’ll define and describe RNNs generally, focusing on the limitations of vanilla RNNs that led to the development of the LSTM.
We’ll describe the intuitions behind the LSTM architecture, which will enable us to build up to and derive the LSTM. Along the way we will derive the GRU. We’ll also derive a pseudo LSTM, which we’ll see is better in principle and

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README.md

What is it …

mdmath allows to use Visual Studio Code as a markdown editor capable of typesetting and rendering TeX math.
In fact it functions and renders identically to the built in markdown viewer. Additionally KaTeX works inside as a fast math renderer.

You can install the extension directly from Visual Studio Code Marketplace.

Release 1.0 published with support of …

Formula numbers.
Footnotes

Features

Simplify the process of authoring and live previewing markdown documents containing math formulas.
This extension is a comfortable tool for scientists, engineers and students with markdown as their first choice
document format.

Inline math by $ … $
Display math by $$ … $$
Add formula numbering by $$ … $$ (1)
Inline math with tables
Embedded HTML
Syntax highlighting with code sections
Export resulting HTML code for web usage
Test Table

Some math expressions are collected in a test table.

Installation …

… from inside of VSCode

Press F1 key inside of Visual Studio Code and type extension. Choose Extensions:

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