Data Science

Open-source projects categorized as Data Science
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Language: + Python + Jupyter Notebook + HTML + TypeScript + JavaScript
Topics: Machine Learning Python Deep Learning Data Analysis Data Visualization
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Top 23 Data Science Open-Source Projects

  • ML-For-Beginners

    12 weeks, 26 lessons, 52 quizzes, classic Machine Learning for all

    • Project mention: Good coding groups for black women? | news.ycombinator.com | 2024-01-13

    - https://github.com/microsoft/ML-For-Beginners

    Also check out this list Pitt puts out every year:

  • Keras

    Deep Learning for humans

    • Project mention: Library for Machine learning and quantum computing | dev.to | 2024-04-27

    Keras

  • InfluxDB

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  • superset

    Apache Superset is a Data Visualization and Data Exploration Platform

    • Project mention: Apache Superset | news.ycombinator.com | 2024-02-26

    Superset is absolutely phenomenal. I really hope Microsoft eventually releases all of their customizations they made to it internally to the OS community someday.

    https://www.youtube.com/watch?v=RY0SSvSUkMA

    https://github.com/apache/superset/discussions/20094

  • scikit-learn

    scikit-learn: machine learning in Python

    • Project mention: AutoCodeRover resolves 22% of real-world GitHub in SWE-bench lite | news.ycombinator.com | 2024-04-09

    Thank you for your interest. There are some interesting examples in the SWE-bench-lite benchmark which are resolved by AutoCodeRover:

    - From sympy: https://github.com/sympy/sympy/issues/13643. AutoCodeRover's patch for it: https://github.com/nus-apr/auto-code-rover/blob/main/results...

    - Another one from scikit-learn: https://github.com/scikit-learn/scikit-learn/issues/13070. AutoCodeRover's patch (https://github.com/nus-apr/auto-code-rover/blob/main/results...) modified a few lines below (compared to the developer patch) and wrote a different comment.

    There are more examples in the results directory (https://github.com/nus-apr/auto-code-rover/tree/main/results).

  • Pandas

    Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

    • Project mention: AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions | dev.to | 2024-04-28

    Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience.

  • Made-With-ML

    Learn how to design, develop, deploy and iterate on production-grade ML applications.

    • Project mention: [D] How do you keep up to date on Machine Learning? | /r/learnmachinelearning | 2023-08-13

    Made With ML

  • Airflow

    Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

    • Project mention: Building in Public: Leveraging Tublian's AI Copilot for My Open Source Contributions | dev.to | 2024-02-12

    Contributing to Apache Airflow's open-source project immersed me in collaborative coding. Experienced maintainers rigorously reviewed my contributions, providing constructive feedback. This ongoing dialogue refined the codebase and honed my understanding of best practices.

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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  • streamlit

    Streamlit — A faster way to build and share data apps.

    • Project mention: Creando Subtítulos Automáticos para Vídeos con Python, Faster-Whisper, FFmpeg, Streamlit, Pillow | dev.to | 2024-04-29

    Streamlit (https://streamlit.io/)

  • Ray

    Ray is a unified framework for scaling AI and Python applications. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

    • Project mention: Open Source Advent Fun Wraps Up! | dev.to | 2024-01-05

    22. Ray | Github | tutorial

  • gradio

    Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

    • Project mention: AI enthusiasm #9 - A multilingual chatbot📣🈸 | dev.to | 2024-05-01

    gradio is a package developed to ease the development of app interfaces in python and other languages (GitHub)

  • spaCy

    💫 Industrial-strength Natural Language Processing (NLP) in Python

    • Project mention: Step by step guide to create customized chatbot by using spaCy (Python NLP library) | dev.to | 2024-03-23

    Hi Community, In this article, I will demonstrate below steps to create your own chatbot by using spaCy (spaCy is an open-source software library for advanced natural language processing, written in the programming languages Python and Cython):

  • AI-Expert-Roadmap

    Roadmap to becoming an Artificial Intelligence Expert in 2022

    • Project mention: Best AI ML DL DS Roadmap | /r/deeplearning | 2023-12-07

    **[I.am.ai AI Expert Roadmap](https://i.am.ai/roadmap)**: This roadmap focuses more on AI and includes various aspects of machine learning and deep learning. It's suitable for those who want to delve deeper into AI, particularly in cutting-edge research and applications.

  • pytorch-lightning

    Pretrain, finetune and deploy AI models on multiple GPUs, TPUs with zero code changes.

    • Project mention: SB-1047 will stifle open-source AI and decrease safety | news.ycombinator.com | 2024-04-29

    It's very easy to get started, right in your Terminal, no fees! No credit card at all.

    And there are cloud providers like https://replicate.com/ and https://lightning.ai/ that will let you use your LLM via an API key just like you did with OpenAI if you need that.

    You don't need OpenAI - nobody does.

  • data-science-ipython-notebooks

    Data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe, Keras), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.

  • Data-Science-For-Beginners

    10 Weeks, 20 Lessons, Data Science for All!

    • Project mention: Welcome to 14 days of Data Science! | dev.to | 2024-03-07

    Get started with Data Science in the Data Science for Beginners curricula.

  • Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

    aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)

    • Project mention: Probabilistic Programming and Bayesian Methods for Hackers (2013) | news.ycombinator.com | 2024-02-10

  • applied-ml

    📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.

  • awesome-datascience

    :memo: An awesome Data Science repository to learn and apply for real world problems.

    • Project mention: About Data analyst, data scientist and data engineer, resources and experiences | dev.to | 2024-03-26

    Awesome Data Science by Academic

  • ML-From-Scratch

    Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

  • d2l-en

    Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

  • fastbook

    The fastai book, published as Jupyter Notebooks

    • Project mention: The fastai book, published as Jupyter Notebooks | news.ycombinator.com | 2024-01-17

  • dash

    Data Apps & Dashboards for Python. No JavaScript Required.

    • Project mention: dash VS solara - a user suggested alternative | libhunt.com/r/dash | 2023-10-13

  • matplotlib

    matplotlib: plotting with Python

    • Project mention: How and where is matplotlib package making use of PySide? | /r/learnpython | 2023-12-07

  • SaaSHub

    SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives

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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).

Data Science related posts

Index

What are some of the best open-source Data Science projects? This list will help you:

Project Stars
1 ML-For-Beginners 66,908
2 Keras 60,937
3 superset 58,852
4 scikit-learn 58,130
5 Pandas 41,983
6 Made-With-ML 35,656
7 Airflow 34,485
8 streamlit 31,717
9 Ray 31,101
10 gradio 28,987
11 spaCy 28,751
12 AI-Expert-Roadmap 28,418
13 pytorch-lightning 26,883
14 data-science-ipython-notebooks 26,490
15 Data-Science-For-Beginners 26,392
16 Probabilistic-Programming-and-Bayesian-Methods-for-Hackers 26,362
17 applied-ml 25,984
18 awesome-datascience 23,777
19 ML-From-Scratch 23,189
20 d2l-en 21,704
21 fastbook 20,749
22 dash 20,502
23 matplotlib 19,262

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