pgmpy

It’s been a year since we launched FLOSS/fund, an initiative to provide no-strings-attached funding to Free and Open Source projects, and to make it easier to discover and support global critical infrastructure. We are announcing the second and final tranche for FLOSS/fund's $1 million commitment for 2025. Read more about our second tranche, anniversary reflections and future plans - https://lnkd.in/gk5ybUte Blender Crystal Dokku dotenvx Ente F-Droid FFmpeg freeCodeCamp Gleam ✨ Graphile Humanitarian OpenStreetMap Team KDE e.V. Kiwix offline LFortran The Matrix.org Foundation Tarides OpenRefine OpenStreetMap Foundation pgmpy PocketBase postmarketOS quic-go Rethink DNS Sequoia PGP Tus Vale Wireshark Foundation Yjs Zen Browser Zerodha FOSS United

We would like to thank FLOSS/fund and Zerodha for the $10k donation to pgmpy. Announcement blogpost: https://lnkd.in/gk5ybUte #pgmpy #OpenSource #Python #CausalInference

🌟 Join the pgmpy Reading Club! We’re excited to launch a new Reading Club as part of our Thursday Community Meeting series. This initiative is designed for beginners and enthusiasts who want to explore causal inference in an accessible, discussion driven format. For our first session, we’ll be diving into Chapter 1: The Ladder of Causation from Judea Pearl’s acclaimed book, The Book of Why. 💡 What to Expect • A guided discussion led by Aheli Poddar • Simple explanations for newcomers • Space to ask questions, share insights and connect with others learning causal inference • A welcoming community for anyone curious about probabilistic graphical models and reasoning under uncertainty 🗓️ Date: Thursday, 21st August 2025 ⏰ Time: 10:00 PM IST | 4:30 PM UTC 📍 Location: https://lnkd.in/dvKkSYVX Whether you’re a researcher, data scientist, student or just curious about why things happen, this is the perfect place to start. 🔗 Save the date, read the chapter and come ready to discuss! #pgmpy #CausalInference #GraphicalModels #MachineLearning #BookClub #ReadingClub #TheBookOfWhy #JudeaPearl #OpenSource #CommunityEvent

This one means a lot! I’m happy to share that I’ve been selected for the European Summer of Code 2025, with Electrolux Group! Over the next few months, I’ll be working on the “Causal AI for Time Series” project under the mentorship of Franz Király, Marc Rovira and Ankur Ankan exploring how causal models can be used to improve supply chains, pricing and production planning. A huge thanks to the wonderful people at European Summer of Code, Electrolux Group, German Center for Open Source AI for making this space for young developers to learn, build and grow. Super excited for what’s ahead ✨ 🔗 Project: https://lnkd.in/dJ9hZX-B 🔗 Program: https://esoc.dev 🔗 sktime: https://github.com/sktime 🔗 pgmpy: https://github.com/pgmpy #EuropeanSummerOfCode #CausalAI #OpenSource #ESoC2025 #TimeSeries

Machine learning is good at prediction... but understanding cause and effect? That's the realm of causal inference and probabilistic modeling. Want to explore this new realm of reasoning under uncertainty and causal discovery? We’re welcoming contributors at pgmpy, a Python library for probabilistic graphical modeling and causal inference. If you're exploring the world of open source or looking to deepen your skills, there are good first issues ready for you to tackle. Whether you're a student or an experienced contributor, you're welcome to pick a "good first issue" or any open issue that excites you. Browse here on Github: https://github.com/pgmpy Join our Discord channel to connect with the community: https://lnkd.in/efVa6KGw We also have mentored projects and deeper collaboration opportunities for contributors who demonstrate initiative and good quality work. 🚀 #opensource #causalinference #pgmpy #machinelearning #probabilisticmodels #python

Machine learning is good at prediction... but understanding cause and effect? That's the realm of causal inference and probabilistic modeling. Want to explore this new realm of reasoning under uncertainty and causal discovery? We’re welcoming contributors at pgmpy, a Python library for probabilistic graphical modeling and causal inference. If you're exploring the world of open source or looking to deepen your skills, there are good first issues ready for you to tackle. Whether you're a student or an experienced contributor, you're welcome to pick a "good first issue" or any open issue that excites you. Browse here on Github: https://github.com/pgmpy Join our Discord channel to connect with the community: https://lnkd.in/efVa6KGw We also have mentored projects and deeper collaboration opportunities for contributors who demonstrate initiative and good quality work. 🚀 #opensource #causalinference #pgmpy #machinelearning #probabilisticmodels #python

We're excited to announce Mohammed Abdul Razak Wahab, our third speaker for tomorrow – presenting a lightning talk! In this brief session, Mohammed will introduce Causal Machine Learning (Causal ML) and its key differences from predictive ML, with a focus on answering interventional and counterfactual "what-if" questions. The talk will also feature pgmpy, an open-source Python library for causal and probabilistic inference, with real-world use cases and applications. Mohammed is currently contributing to pgmpy as part of the European Summer of Code programme! Talk: Introduction to Causal Machine Learning and pgmpy Date: 26th July 2025, Online Time: 10AM–1PM IST RSVP here: https://lnkd.in/gfQNwEpw 📣 Help us spread the word by resharing this post with your network! 💬 Join the Zulip community chat: https://lnkd.in/gvPxiHfh 📢 Follow us on our social media handles: LinkedIn: SciPy India Bluesky: https://lnkd.in/gP7cdtmc Mastodon: https://lnkd.in/gj2xHN-z PyCon India 2025 Python Software Foundation Scientific Python Scipy SciPy Conference EuroPython PyDelhi MumPy Hyderabad Python Users Group Chennaipy FOSS United Bangpypers Data Umbrella NumFOCUS PyData Delhi PyData PyData Bangalore PyData Mumbai PyData Global Open Source Science Initiative (OSSci) Rust Delhi Rust India pyOpenSci FOSS United Delhi FOSS United Bangalore FOSS United Hyderabad FOSS United Chennai

Dear Linkedin Community! I am proud to announce that I have been accepted into the European Summer of Code program for the third batch of projects and I will be working with the pgmpy organization under Ankur Ankan. A brief description would be implementation of MAGs (Maximal Ancestral Graphs) and PAGs (Partial Ancestral Graphs) for pgmpy. For those have come across this program for the first time, it is an open source program, very similar to your typical Google Summer of Code where a batch of projects are released and candidates apply based on which organization they are interested in working with. More details can be found on its official website : https://www.esoc.dev/ #opensource #ESOC #Sktime #pgmpy

pgmpy joins the German Center for Open Source AI! We are happy to welcome and support pgmpy, the leading python package for causal AI and probabilistic graphical modelling!   pgmpy enables users to perform tasks such as modelling supply/demand mechanisms, inferring equipment failure chains in factory systems, or learning causal relationships from epidemiological data. pgmpy provides users with a clean API for with support for structure learning from raw datasets, exact and approximate inference algorithms, model construction, and visualization. pgmpy equips data scientists, researchers, and engineers with a broad set of tools for causal AI, all with a consistent and interoperable software interface. pgmpy is open source, permissive license, and maintained by a distributed community of developers and users. Join a growing community of practice for causal learning. Meet the community on the official discord https://lnkd.in/eumv3M_B or look at the tutorials on the pgmpy website: https://lnkd.in/eGrC5wq5   If you are interested to contribute, visit the Discord and GitHub for good first issues: https://lnkd.in/eVMjeEH6 pgmpy is also featured as a project at European Summer of Code: https://esoc.dev contributors new to open source and interested in causal AI should apply!   #pgmpy #opensource #python #ai #ki

🚀 New European Summer of Code project, with Electrolux Group - Causal Learning for Time Series. Build the open source AI landscape for causal AI in time series, with applications across supply chain management and retail! Application deadline June 12, 18:00 UTC. Causal time series models are central to many industry grade use cases in production, retail, and supply chain. Join Electrolux and the German Center for Open Source AI to start building an interoperable, open-source ecosystem of causal tools for forecasting and structure identification - in collaboration with pgmpy and sktime. Detail description and application process - deadline June 12 https://lnkd.in/dFW4JymJ ESoC webpage: https://www.esoc.dev/ #ESoC #OpenSource #AI #Internship #TechForGood