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@nerzhulart
nerzhulart / Windows Defender Exclusions for Developer.ps1
Last active October 10, 2025 11:29 — forked from dknoodle/Windows Defender Exclusions VS 2017.ps1
Adds Windows Defender exclusions for developers (Visual Studio, JetBrains Rider, IntellIJ Idea, Git, MsBuild, dotnet, mono etc.)
$userPath = $env:USERPROFILE
$pathExclusions = New-Object System.Collections.ArrayList
$processExclusions = New-Object System.Collections.ArrayList
$pathExclusions.Add('C:\Windows\Microsoft.NET') > $null
$pathExclusions.Add('C:\Windows\assembly') > $null
$pathExclusions.Add($userPath + '\AppData\Local\Microsoft\VisualStudio') > $null
$pathExclusions.Add('C:\ProgramData\Microsoft\VisualStudio\Packages') > $null
$pathExclusions.Add('C:\Program Files (x86)\MSBuild') > $null
$pathExclusions.Add('C:\Program Files (x86)\Microsoft Visual Studio 14.0') > $null
@JesterXL
JesterXL / Streams in JavaScript Sample Code.md
Last active March 29, 2018 13:49
Streams in JavaScript Sample Code

Streams in JavaScript

The slides for this code.

If you're trying to learn the basics of the Array methods, this thorough tutorial with answers is a great place to start.

Found some WONDERFUL documentation if you're curious what type of observable to use or method to use on your data. It shows it in a big table of user stories.

Lee Campbell has some examples as well.

@debasishg
debasishg / gist:8172796
Last active October 3, 2025 16:28
A collection of links for streaming algorithms and data structures

General Background and Overview

  1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
  2. Models and Issues in Data Stream Systems
  3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
  4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
  5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t