Get data science and machine learning production insights from top companies, for startup founders, with 30k+ GitHub stars.
intermediateโฑ 30 minutes๐ต Free
29,927 stars3,970 forksQuality 9/10Updated 7/18/2024100% free ยท open source
What it is
Reads and shares papers by companies about data science and machine learning.
What you can make with it
Your own in-depth guides to data science and machine learning in production, using insights from real companies.
How it helps
Helps you stay up-to-date with the latest advancements in data science and machine learning, and understand how companies apply them in production.
Real use case example
"A founder needs to implement a recommendation engine for their e-commerce site. They browse through papers on applied machine learning, note the key techniques, and use them to build their engine."
If you're new
Pick this up when you first start exploring data science and machine learning concepts.
If you're senior
Use this when you need inspiration or insights on complex data science or machine learning projects.
Common confusion cleared up
This skill does not provide a direct AI model or toolset, but rather shares insights and papers on data science and machine learning in production.
Best inside these AI tools
Any AI Client
Pairs with
Claude APIStripe webhookNotion database
Why we list it on WorkflowStacks: A marketplace of AI tools that offers free and open-source access to papers and tech blogs on data science and machine learning.
What it does
Applied-ml is a collection of papers and tech blogs from companies showcasing their data science and machine learning work in production, providing insights and knowledge for startups to learn from.
Install / run
Clone the repository using the command `git clone https://github.com/eugeneyan/applied-ml.git`
When to use it
โขWhen researching how to apply machine learning to a specific business problem
โขWhen looking for inspiration and examples of real-world machine learning applications
โขWhen trying to stay up-to-date with the latest developments and advancements in the field of machine learning
Quick start
1Explore the repository by navigating to the cloned directory using `cd applied-ml`
2Open the `README.md` file to get an overview of the collection and its contents
3Browse through the various subdirectories, such as `companies` and `papers`, to find relevant resources
4Use the `README.md` file as a starting point to discover new companies and research papers
5Search for specific topics or keywords within the repository using `grep` or a similar tool
Ready-to-paste prompt
Search for papers related to natural language processing using `grep -r 'natural language' *` within the repository
Heads up: The repository is a collection of external links and resources, so be aware that some links may be broken or outdated, and it's essential to verify the information and sources before using them
Saves to your device
Topics
applied-data-science
applied-machine-learning
computer-vision
data-discovery
data-engineering
data-quality
data-science
deep-learning
machine-learning
natural-language-processing
production
recsys
reinforcement-learning
search
What's inside โ free to inspect
No purchase needed
Read the entire source before you build โ unlike paid marketplaces that hide it behind a buy button.