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Top 23 HTML Machine Learning Projects
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Project mention: Microsoft's Open-Source ML Curriculum Is Best to Learn ML from Scratch | news.ycombinator.com | 2025-04-07
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InfluxDB
InfluxDB high-performance time series database. Collect, organize, and act on massive volumes of high-resolution data to power real-time intelligent systems.
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deep-learning-drizzle
Drench yourself in Deep Learning, Reinforcement Learning, Machine Learning, Computer Vision, and NLP by learning from these exciting lectures!!
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unstructured
Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.
I've been thinking a lot about how to accomplish various RAG things in Elixir (for LLM applications). PDF is one of the missing pieces, so glad to see work here. The really tricky part is not just parsing out the text (you can just call the pdftotext unix command line utility for that), but accurately pulling out things like complex tables, etc in a way that could be chunked/post processed in a useful way. I'd love to see something like Unstructured or Marker but in Rust that Elixir could NIF out to it.
- https://github.com/Unstructured-IO/unstructured#eight_pointe...
- https://github.com/VikParuchuri/marker
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Project mention: Comprehensive Data Science Interview Guide: Questions and Answers Repository | news.ycombinator.com | 2024-09-03
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seldon-core
An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models
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CodeRabbit
CodeRabbit: AI Code Reviews for Developers. Revolutionize your code reviews with AI. CodeRabbit offers PR summaries, code walkthroughs, 1-click suggestions, and AST-based analysis. Boost productivity and code quality across all major languages with each PR.
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Project mention: Apache Mahout: A Deep Dive into Open Source Innovation and Funding Models | dev.to | 2025-03-06
The journey of Apache Mahout highlights several key aspects that make it a standout example in the open source community. First, the project’s roots in scalable machine learning address real-world data processing challenges and have evolved by leveraging a thriving contributor network. This success is bolstered by the comprehensive governance provided by the Apache Software Foundation, which ensures that community standards and development protocols are strictly followed. Funding for Apache Mahout is an amalgamation of traditional methods and modern alternatives. While corporate sponsorships and donations remain the primary funding channels, innovative token-based approaches are emerging as a supplementary resource. These methods use blockchain technology to create transparent financial flows and offer new layers of accountability and incentive for contributors. Equally important is the Apache 2.0 license. This permissive and protective license not only allows developers the freedom to modify and distribute the software but also includes a strong patent grant that reduces the risk of legal disputes. The balance achieved by combining a robust open source license framework with both conventional and innovative funding approaches is paving the way for a brighter, more sustainable future in open source development. Moreover, the project’s core principles, such as meritocracy, transparency, and community engagement, make it a model that many other projects can learn from. By hosting its code on platforms like GitHub and maintaining detailed documentation, Apache Mahout invites both seasoned developers and enthusiastic newcomers to explore, contribute, and benefit from its continuously growing repository of knowledge.
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awesome-streamlit
The purpose of this project is to share knowledge on how awesome Streamlit is and can be
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TradingView-Machine-Learning-GUI
Embark on a trading journey with this project's cutting-edge stop loss/take profit generator, fine-tuning your TradingView strategy to perfection. Harness the power of sklearn's machine learning algorithms to unlock unparalleled strategy optimization and unleash your trading potential.
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awesome-python
🐍 Hand-picked awesome Python libraries and frameworks, organised by category (by dylanhogg)
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extractnet
A fork of Dragnet that also extract author, headline, date, keywords from context, as well as built in metadata extraction all in one package
Hmm, extractnet seems promising:
https://github.com/currentslab/extractnet
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cs229-2019-summer
All notes and materials for the CS229: Machine Learning course by Stanford University
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The instructions are on their GitHub page
https://github.com/SKKU-SecLab/AdFlush/tree/main?tab=readme-...
But since the first webpage I tried still had huge ads, I turned uBlock back on ;)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
NOTE:
The open source projects on this list are ordered by number of github stars.
The number of mentions indicates repo mentiontions in the last 12 Months or
since we started tracking (Dec 2020).
HTML Machine Learning discussion
HTML Machine Learning related posts
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Demos for "Linear Algebra for DS, ML, and SP" Book in Julia
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Microsoft's Open-Source ML Curriculum Is Best to Learn ML from Scratch
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Neural DSL v0.2.6: Enhanced Dashboard UI & Blog Support
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Apache Mahout: A Deep Dive into Open Source Innovation and Funding Models
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Let Claude read your Gas Meter with this Amazing new Feature
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Comprehensive Data Science Interview Guide: Questions and Answers Repository
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LLMs for Report Validation
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A note from our sponsor - InfluxDB
influxdata.com | 23 Apr 2025
Index
What are some of the best open-source Machine Learning projects in HTML? This list will help you:
| # | Project | Stars |
|---|---|---|
| 1 | ML-For-Beginners | 71,894 |
| 2 | deep-learning-drizzle | 12,547 |
| 3 | Awesome-Diffusion-Models | 11,661 |
| 4 | unstructured | 10,920 |
| 5 | data-science-interviews | 9,265 |
| 6 | kaggle-solutions | 5,297 |
| 7 | seldon-core | 4,502 |
| 8 | awesome-mlss | 2,759 |
| 9 | Apache Mahout | 2,162 |
| 10 | awesome-streamlit | 2,128 |
| 11 | WikiSQL | 1,722 |
| 12 | papers-I-read | 945 |
| 13 | ML-University | 888 |
| 14 | TradingView-Machine-Learning-GUI | 796 |
| 15 | bio_embeddings | 474 |
| 16 | awesome-python | 377 |
| 17 | extractnet | 272 |
| 18 | GBM-perf | 217 |
| 19 | cs229-2019-summer | 210 |
| 20 | dkm | 95 |
| 21 | Open-Source-Gallery | 85 |
| 22 | DeepCite | 69 |
| 23 | AdFlush | 58 |
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