This collection links community detection research papers and their implementations.
The Best Applied ML Alternatives in 2026
Looking for something like Applied ML? Here are 24 alternatives, ranked by how closely they match it on purpose, features and platforms. Of these, 1 are free or have a free plan and 13 are open source.
This repository collects company papers and technical blogs about machine learning in production.
Top picks at a glance
Quick comparison
| # | Alternative | Pricing | Open source | Platforms |
|---|---|---|---|---|
| 1 | Awesome Community Detection | — | Yes | — |
| 2 | AlexChalakov/awesome-generative-ai-companies | — | Yes | — |
| 3 | Awesome Machine Learning with Ruby | — | Yes | — |
| 4 | Awesome Core ML Models | — | Yes | iOS, macOS |
| 5 | Awesome RAG Production | — | Yes | — |
| 6 | Awesome AI Market Maps | — | Yes | — |
| 7 | Stackwise | — | Yes | — |
| 8 | Awesome Federated Learning Systems | — | Not stated | — |
| 9 | Awesome Machine Learning | — | Not stated | — |
| 10 | Awesome TensorFlow | — | Yes | Android |
All Applied ML alternatives
AlexChalakov/awesome-generative-ai-companies
github.com/AlexChalakov/awesome-generative-ai-…Open sourceA curated list of Gеnerative AI companies, sorted by focus area and total fundraised amount.
This repository collects machine learning resources and tools for the Ruby programming language.
Browse a list of machine learning models for Apple Core ML, collected in this repository.
Awesome RAG Production curates tools, frameworks, and practices for building retrieval-augmented generation systems.
Awesome AI Market Maps collects market maps about AI from 2025 and 2026.
Stackwise collects open-source AI applications and invites community contributions to its project.
Awesome Federated Learning Systems
github.com/AmberLJC/FLsystem-paper/blob/main/R…This repository curates academic papers and related resources about federated learning systems.
Awesome Machine Learning
github.com/josephmisiti/awesome-machine-learningA curated list of machine learning frameworks, libraries, and software maintained in a GitHub repository.
Awesome TensorFlow lists experiments, libraries, and projects related to TensorFlow.
Awesome AI Books
github.com/mahseema/aibooksAwesome AI Books curates books about artificial intelligence, machine learning, deep learning, and transformers.
machine-learning-zoomcamp
github.com/DataTalksClub/machine-learning-zoom…Machine Learning Zoomcamp teaches machine learning engineering through a course and registration materials.
Community Curated Data Science Resources
hackr.io/tutorials/learn-data-scienceThis catalog curates data science courses, tutorials, books, and other learning resources.
awesome-r
github.com/qinwf/awesome-RExplore packages, frameworks, and software in Awesome R, a curated resource list for the R ecosystem.
ML Resources
ml-resources.vercel.appA collection of machine learning resources for readers exploring the field.
Browse a curated list of artificial intelligence tools in this repository.
PromptEngineering
github.com/NirDiamant/Prompt_EngineeringThis repository teaches 22 prompt engineering techniques through Jupyter Notebook tutorials.
LocalModelsLinks
rentry.org/LocalModelsLinksLocalModelsLinks collects guides and references for running and tuning language models locally.
Screenpipe
github.com/mediar-ai/screenpipeScreenpipe records screen activity locally and provides context to AI agents.
Awesome AI Models curates links to AI models and large language models.
Prompt Engineering Guide collects lessons, papers, notebooks, and resources on prompting, retrieval-augmented generation, and AI agents.
SpeechMap data stores versioned model responses and production compliance analyses.
This repository collects references for vibe coding, where AI helps write code.
This repository collects tools and resources for vibe coding with AI assistance.
Alternatives to similar tools
What is the best alternative to Applied ML?
Is there a free alternative to Applied ML?
Are there open-source alternatives to Applied ML?
Alternatives are suggested from the purpose and features described in our listings. Different pages for the same product appear once. Read each description to check whether it fits your task. How we choose alternatives · Suggest an alternative
























