applied-ml
PowerToys
applied-ml | PowerToys | |
---|---|---|
13 | 713 | |
25,984 | 104,500 | |
- | 1.1% | |
3.0 | 9.8 | |
5 days ago | 5 days ago | |
C# | ||
MIT License | MIT License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
applied-ml
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[D] Favorite ML Youtube Channels/Blogs/Newsletters
Also, have any of you stumbled across any cool GitHub repos like this one: https://github.com/eugeneyan/applied-ml ?
- Curated Papers on Machine Learning in Production
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Top Github repo trends in 2021
The second repo I LOVE is Eugene Yan’s Applied ML repository. This is a brilliant idea to create and actually something I was planning on sort of casually doing in my non-existent free time… Anyhow, it is a curated list of technical posts from top engineering teams (Netflix, Amazon, Pinterest, Linkedin, etc.) detailing how they built out different types of AI/ML systems (e.g. forecasting, recommenders, search and ranking, etc.). Ofc, it focuses on AI/ML, but something similar could be made for the traditional or BI-oriented analytics stack, as well as the streaming world, super high value for practitioners! Btw-one of my favorite things at BCG used to be looking at our IT architecture team’s reference architecture diagrams… the best way to understand technologies is to look at how a ton of stuff is architected… and its fun!
- Curated papers, articles, & blogs on data science and ML in production
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Messed up my career by pivoting to DS. Wondering if it's too late to switch to MLE
Applied ML: A collection of papers, articles, and blogs on ML in production by different companies (Netflix, Uber, Facebook, LinkedIn, etc)
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[D] A dilemma of an ML guy in industry
Eugene Yan's applied-ml has tons of case studies.
- Papers & tech blogs by companies sharing their work on data science & machine learning in production.
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My information dump for people trying to break into data science/interview notes
https://github.com/eugeneyan/applied-ml You may find some of his links interesting. I would avoid anything that refers to scaling up a platform as these are more backend engr focus. The more relevant posts to you are probably on the scale of blog posts that are product oriented like the ones I listed in section 4 (e.g. we wanted to solve X for our users and this is how we scoped and defined it). The technical aspects should come backseat to the business aspects. There's def a lot of companies/blog posts that he missed, but the internet is huge.
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[D] Can anyone point me to resources/case studies of companies/business creating infrastructure for their data needs?
Check the resources mentioned in applied-ml. It includes blog posts/papers from many companies describing how they built some ML product X.
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What content would be useful to intermediate Data Scientist
Check out this repo. They collect hundreds of case studies, broken down by dozens of methodologies from large real-world companies such as AirBnB, Nvidia, Uber, Netflix etc.
PowerToys
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Unlock Web Dev Superpowers with PowerToys
Windows PowerToys GitHub Repo
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We released a new powerful efficiency tool called RunFlow, which is similar to PowerToys and Alfred, welcome to try it
RunFlow is a cross-platform productivity tool which can launch apps and search files and more, that similar to Wox and PowerToys on Windows, and also similar like Alfred and Raycast on macOS. But we have differences with these tools, and we have our own unique new features. Right now, at the below, we will introduce you what features of RunFlow have been implemented in more details. It's an amazing journey, let's start.
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GTK: On fractional scales, fonts and hinting
I'm curious - when you were doing research into the mechanics of hinting options, did you stumble onto any relevant discussion around allowing custom pixel geometries to be defined, to enable hinting on modern OLED / WRBG displays? There's a good thread on the topic here[0], with some people referring to it as 'ClearType 2' on the MS side [1]. On the oss side I know FreeType theoretically supports this[2], but I can't quite figure out how relevant the FreeType backend is to this most recent work.
This is great work btw.
[0]: https://github.com/snowie2000/mactype/issues/932
[1]: https://github.com/microsoft/PowerToys/issues/25595
[2]: https://freetype.org/freetype2/docs/reference/ft2-lcd_render...
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Ask HN: Cleanest way to manage Windows OS?
Thank you all for the informative advices. Here is the summary for those who are in the same situation:
1. Run Windows on Linux by using VM
for the applications you can’t run on Linux
Risks:
* some softwares may attempt to detect VMs and refuse running
* Anything what needs to touch hardware may not work.
2. separate "data" partition on D:
3. back up %APPDATA% and %USERPROFILE%
4. learn chocolatey, scoop or winget
Winget should be good enough
5. Don’t worry about C:\Program Files
6. (Mixed) Use/Don’t use Ansible (or saltstack/salt)
Use:
* Allows you to setup a new machine quickly and consistently when one breaks, get stolen, or lost in an inconvenient time.
* You can get a clean and consistent development environment so that you do not depend on anything accidentally installed on the machine.
* If you define specialised roles, create test playbooks for those individual roles, use these roles to compose more complex playbooks, and offload logic to custom ansible modules that are written in python, you won't wrestle with heavy logic in the template or playbook layer.
* installing software and pulling some configs and scripts down is fine
Don’t use:
* You will spend your days fighting a mix of yaml and Jinja.
* You will end up looking at Python errors because there are no static types.
* errors are cryptic.
7. Use WSL2
You need 32gb of ram, but ram is cheap so choose a good thinkpad
8. Debloat with Recommended Tweaks
Run
irm christitus.com/win | iex
from Administrator Terminal (Powershell)
The link leads to https://raw.githubusercontent.com/ChrisTitusTech/winutil/mai...
VirusTotal
https://www.virustotal.com/gui/file/709834b0e003b6bb546cf16e...
9. Get [PowerToys](https://github.com/microsoft/PowerToys)
10. Use Devbox for containered environment
https://www.jetpack.io/devbox
11. Dual-Booting Linux and Windows
If you use physically separated drives, you don’t need partitioning.
12. Dedicated Windows machine for class
Yes it sure would be the cleanest solution but I prefer one device for everything
13. keep a git repository with all dot files in it
Many people suggested me to use virtualization, otherwise just let Windows be Windows.
Also, backing up seems to be a good practice.
I’m planning to write a blog about this, if it worked.
Again, thank you all for the helps!
- Ask HN: Best Hacks for a Ultrawide Monitor?
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Keypirinha: A fast launcher for keyboard ninjas on Windows
Powertoys Run (https://github.com/microsoft/powertoys) can do this. There are not that many plugins as Alfred but Window Switcher is built-in.
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LAN Mouse is a mouse and keyboard sharing software
For sharing a mouse/keyboard between Windows PCs, there is Mouse Without Borders. It's included in PowerToys nowadays.
https://github.com/microsoft/PowerToys
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Hrvach/Deskhop: Fast Desktop Switching Device
- https://github.com/microsoft/PowerToys
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How do I type letters with accent marks?
If you’re on Windows, download PowerToys. It’s an app published by Microsoft officially. Then enable Quick Accent in the settings of PowerToys. Now all you have to do is hold down the key you want accented until the switch shows up, then add an accent with your arrow keys.
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Microsoft's Powertoys Key Manager now can paste text and unicode by shortcuts
microsoft/PowerToys: Windows system utilities to maximize productivity (github.com)
What are some alternatives?
awesome-mlops - A curated list of references for MLOps
Wox - A cross-platform launcher that simply works
awesome-ml-blogs - Curated list of technical blogs on machine learning · AI/ML/DL/CV/NLP/MLOps
AutoHotkey - AutoHotkey - macro-creation and automation-oriented scripting utility for Windows.
machine-learning-roadmap - A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
sharpkeys - SharpKeys is a utility that manages a Registry key that allows Windows to remap one key to any other key.
Cookbook - The Data Engineering Cookbook
Flow.Launcher - :mag: Quick file search & app launcher for Windows with community-made plugins
ml-surveys - đź“‹ Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
Fluent-Search - Official repository for Fluent Search, use to report issues or ask for a new feature
pipebase - data integration framework
T-Clock - Highly configurable Windows taskbar clock