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Top 23 Mathematic Open-Source Projects
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JavaScript
Algorithms and Data Structures implemented in JavaScript for beginners, following best practices. (by TheAlgorithms)
4. The Algorithm - Javascript
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C-Plus-Plus
Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.
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SurveyJS
Open-Source JSON Form Builder to Create Dynamic Forms Right in Your App. With SurveyJS form UI libraries, you can build and style forms in a fully-integrated drag & drop form builder, render them in your JS app, and store form submission data in any backend, inc. PHP, ASP.NET Core, and Node.js.
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C
Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.
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Project mention: Algorithmic Alchemy: Exploiting Graph Theory in the Foreign Exchange | dev.to | 2023-10-05
William Fiset's GitHub examples - Bellman Ford On Adjacency Matrix
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InfluxDB
Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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By the way, just for clarity, note that the comments in this subthread were written before we updated the random seed for that example to result in a much better diagram: https://github.com/penrose/penrose/pull/1700
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Project mention: Node still seems better than python after all this time for web server speed but.. | /r/node | 2023-06-20
Numpy is a library - node.js has plenty of them, what is missing? There is stdlib package that offers optimized math functions, for example.
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ML-foundations
Machine Learning Foundations: Linear Algebra, Calculus, Statistics & Computer Science
As others have said, you won't need calculus immediately, but it's important that you make a good attempt at learning up to Calc3. I also didn't have a math heavy undergrad so it took a lot of self-study for me, but it's possible. Simulation has a great math boot camp at the beginning to review everything but you'll want to be prepped with Calc before that because that class is all calculus based probability. Some other good resources are the 3Blue1Brown videos on YouTube. They have a great series for both calc & linear algebra to talk through all the intuition with visuals. I also really like John Krohns series because you code through the math which is very applicable for us in this program. I only did his linear Algebra, but he has a whole series with Calc and probability, too. https://github.com/jonkrohn/ML-foundations
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Project mention: If you can't reproduce the model then it's not open-source | news.ycombinator.com | 2024-01-17
I think the process of data acquisition isn't so clear-cut. Take CERN as an example: they release loads of data from various experiments under the CC0 license [1]. This isn't just a few small datasets for classroom use; we're talking big-league data, like the entire first run data from LHCb [2].
On their portal, they don't just dump the data and leave you to it. They've got guides on analysis and the necessary tools (mostly open source stuff like ROOT [3] and even VMs). This means anyone can dive in. You could potentially discover something new or build on existing experiment analyses. This setup, with open data and tools, ticks the boxes for reproducibility. But does it mean people need to recreate the data themselves?
Ideally, yeah, but realistically, while you could theoretically rebuild the LHC (since most technical details are public), it would take an army of skilled people, billions of dollars, and years to do it.
This contrasts with open source models, where you can retrain models using data to get the weights. But getting hold of the data and the cost to reproduce the weights is usually prohibitive. I get that CERN's approach might seem to counter this, but remember, they're not releasing raw data (which is mostly noise), but a more refined version. Try downloading several petabytes of raw data if not; good luck with that. But for training something like a LLM, you might need the whole dataset, which in many cases have its own problems with copyrights…etc.
[1] https://opendata.cern.ch/docs/terms-of-use
[2] https://opendata.cern.ch/docs/lhcb-releases-entire-run1-data...
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Math PHP
Powerful modern math library for PHP: Features descriptive statistics and regressions; Continuous and discrete probability distributions; Linear algebra with matrices and vectors, Numerical analysis; special mathematical functions; Algebra
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Linear-Algebra-With-Python
Lecture Notes for Linear Algebra Featuring Python. This series of lecture notes will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skillsets. Suitable for statistician/econometrician, quantitative analysts, data scientists and etc. to quickly refresh the linear algebra with the assistance of Python computation and visualization.
Project mention: Python for Econometrics for Practitioners [Free Online Courses] | /r/CompSocial | 2023-08-24Linear Algebra with Python: This training will walk you through all the must-know concepts that set the foundation of data science or advanced quantitative skill sets. Suitable for statisticians, econometricians, quantitative analysts, data scientists, etc. to quickly refresh linear algebra with the assistance of Python computation and visualization. Core concepts covered are: linear combination, vector space, linear transformation, eigenvalues and -vector, diagnolization, singular value decomposition, etc.
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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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Project-Euler-solutions
Runnable code for solving Project Euler problems in Java, Python, Mathematica, Haskell. (by nayuki)
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brick/math: Arbitrary-precision arithmetic library for PHP
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WorkOS
The modern identity platform for B2B SaaS. The APIs are flexible and easy-to-use, supporting authentication, user identity, and complex enterprise features like SSO and SCIM provisioning.
Mathematics related posts
- GeoGebra: A dynamic mathematics software for all levels of education
- Mogan STEM Suite v1.2.5 LTS released
- Harmonics Explorer
- Release of GLM 1.0.0
- Linear Transformers Are Faster After All
- I created an application to visualize hyperdimensional rotating cubes
- I created an application to visualize hyperdimensional rotating cubes
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A note from our sponsor - InfluxDB
www.influxdata.com | 28 Mar 2024
Index
What are some of the best open-source Mathematic projects? This list will help you:
Project | Stars | |
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1 | JavaScript | 30,888 |
2 | C-Plus-Plus | 28,868 |
3 | C | 17,872 |
4 | Algorithms | 16,356 |
5 | MathJax | 9,868 |
6 | GLM | 8,572 |
7 | awesome-math | 8,083 |
8 | penrose | 6,586 |
9 | Mathematics-for-ML | 4,059 |
10 | stdlib | 3,941 |
11 | MathNet | 3,371 |
12 | ML-foundations | 2,859 |
13 | Data-Science-Roadmap | 2,782 |
14 | root | 2,393 |
15 | Computer-Science-Resources | 2,323 |
16 | Math PHP | 2,300 |
17 | texme | 2,244 |
18 | Linear-Algebra-With-Python | 2,098 |
19 | awesome-streamlit | 1,929 |
20 | Project-Euler-solutions | 1,830 |
21 | ml-pen-and-paper-exercises | 1,802 |
22 | meshio | 1,767 |
23 | Brick\Math | 1,722 |