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PyCon US 2025 is coming to Pittsburgh this May 14–22, and PyData Pittsburgh is thrilled to be part of it! We’re hosting the Hometown Heroes Hatchery track on Saturday, May 17—a half-day event inside the conference celebrating the incredible work of Python developers, researchers, educators, and technologists from across our city. As part of PyCon’s Hatchery initiative, this track will feature presentations and lightning talks that highlight the creativity and impact of Pittsburgh’s Python community.

If you're attending PyCon US 2025, we invite the PyData Pittsburgh community to join us at the Hometown Heroes track—come connect, engage, and help showcase the strength of our local tech scene.

Please note: you must be registered for PyCon US 2025 to attend this event, and all attendees and speakers are responsible for securing their own tickets. You can find registration details for the Conference here:https://us.pycon.org/2025/attend/information/.

HOMETOWN HEROES HATCHERY PROGRAM - May 17th

TALK SCHEDULE:

Decoding Spatial Biology with Python: Multi-Modal Insights into Breast Cancer Progression Time: 01:45 PM - 02:15 PM Speakers: Alex C. Chang, CMU-Pitt (Graduate Student PhD, Computational Biology ) and Brent Schlegel, University of Pittsburgh School of Medicine (Graduate Student PhD, Integrative Systems Biology)

Python has rapidly become a cornerstone of scientific computing, computational biology, and bioinformatics due to its ease of use and scalability for handling large datasets—qualities that are critical in today’s “big data” era of clinical and translational research. As computational resources and data collection methods continue to expand, we are now empowered to ask larger and more clinically relevant questions that enable us to dissect complex biological systems with unprecedented detail. However, this surge in data complexity brings new challenges, from the integration of diverse data modalities to the need for sophisticated analytical methods capable of untangling intricate biological signals from background noise. In this talk, we describe how Python not only meets these challenges but also drives innovation through the development of novel bioinformatics tools like CITEgeist—a case study in harnessing Python’s capabilities for multi-modal spatial transcriptomics. Biological datasets often face challenges of high sparsity and noise. CITEgeist harnesses Python’s robust ecosystem to provide an efficient, scalable pipeline that deconvolutes messy spatial signals into actionable, clinically relevant features.

Exploring Energy Burden in Pittsburgh Neighborhoods with Python Time: 02:30 PM - 03:00 PM Speakers: Ling Almoubayyed, SmithGroup, Inc. (Project Manager) and Husni Almoubayyed, Carnegie Learning

National-level energy studies consistently find that energy burdens are a significant challenge, and that lower-income neighborhoods sometimes end up paying more for energy in cities including Pittsburgh. Using Python, we were able to extract and analyze data on energy consumption in the City of Pittsburgh, along with real-estate and geographic information system (GIS) data to compare trends in energy usage and burden across Pittsburgh neighborhoods, and across different housing types. We present statistical analyses and Python visualizations describing these trends across different features such as housing price, size, and neighborhood.

Bottling Tesla's Solar: A Solar Dashboard with Python Time: 03:15 PM - 03:45 PM Speaker: Christopher Pitstick (Sr. SWE)

Tesla's Powerwall/Inverter solar ecosystem are powerful yet notoriously opaque. For home labbers, extracting meaningful data can be daunting—but not impossible. In this talk, I'll share my journey of developing a custom solar dashboard using Grafana and PyPowerwall, navigating the quirks and closed nature of Tesla's ecosystem along the way. The backend is all Python, so I will demo my server code and dashboard to show how I was able find hundreds of kilowatt hours in lost solar production. In this talk, we'll do a deep dive into the way I altered the Python server code to be able to query multiple inverters at the same time with complex iptable rules. This presentation may conclude with the value of installing solar on your home, and how self-monitoring is a critical component of every nerd's arsenal.

Strategies for Eliciting Structured Ouputs from LLMs Time: 03:50 PM - 03:55 PM Speaker: Utkarsh Tripathi, Solventum (Machine Learning Engineer)

This lightning talk will provide a concise yet comprehensive overview of techniques for extracting structured, predictable outputs from Large Language Models. I will compare and demonstrate multiple state-of-the-art libraries (such as BAML, Instructor, Langchain, SGLang etc. + how they work under the hood), utilize pydantic / dataclass / etc. to get structured outputs. We will explore practical examples of JSON schema enforcement, markdown formatting directives, and template-based approaches that dramatically improve downstream processing capabilities. The presentation will include code snippets and prompt templates that participants can immediately implement in their own projects.

Does Generative AI Know Statistics? Time: 03:55 PM - 04:00 PM Speaker: Louis Luangkesorn, Highmark Health (Lead Data Scientist)

Generative AI has promise to impact many fields of endeavor. But experience has shown that it often has problems with nuance and context. This talk discusses some experiences using Generative AI as an aid in applied analytics and walks through an example that illustrates working around its weaknesses and taking advantage of its capabilities.

Demystifying How Animal Behavior Affects Disease Spread Using Python Time: 04:00 PM - 04:05 PM Speaker: Carolyn Tett, University of Pittsburgh (Research Technician)

Not all individuals contribute equally to disease spread. During COVID-19, social distancing reduced transmission for some, while high-contact individuals increased disease spread. Preventative measures for massive disease outbreaks, however, cannot rely solely on data from rare epidemic events. Instead, disease ecologists study animal models to understand how host behavior theoretically drives disease outbreaks. Tracking animal movement and interactions is essential for identifying transmission-relevant behaviors. In lab experiments, video recordings provide an abundance of behavioral data, now efficiently processed through automation, and coding languages like Python enable large-scale data analysis. The Stephenson Lab at the University of Pittsburgh uses Raspberry Pis to autonomously record guppies infected with an ectoparasite. These parasites transmit primarily through instances of close contact between hosts. Through autonomous video recordings, we generated 1,300 hours of footage—equivalent to 54 consecutive days of observation. Given that each video captures six guppies, manually tracking behavior would take tens of billions of days. Instead, animal tracking software reduces this processing time to a mere few months.

The Many-Colored Functions of Async Python Time: 04:15 PM - 04:45 PM Speaker: Bryan C. Mills, Duolingo (Senior Software Engineer)

You might think of functions in async Python in terms of “synchronous” and “async”, but the possibility of binding objects (such as Locks) to the asyncio event loop adds a whole new dimension to consider. We'll examine six vibrant kinds of functions and how they interact! This talk will examine code examples of how to adapt each kind of function to call other kinds, suggest design patterns that minimize the complexity of dealing with different kinds (such as non-blocking context managers), and examine patterns or libraries to safely synchronize concurrent calls involving multiple kinds of function.

Automated Dependency Inference and its Applications Time: 05:00 PM - 05:30 PM Speaker: Jason R. Coombs, Microsoft (Principal Software Engineer)

Last summer, I launched the Coherent Software Development System (https://bit.ly/coherent-system) with the principal that one should not have to repeat themselves when developing more than one Python project. One of the key innovations of that system is coherent.deps, a system for deriving package dependencies from the imports that a project or script uses. I'll explore some of the background motivations from Google's monorepo, some prior art at Meta, and some of the approaches that failed (AI-based inference) before going into the details of the implementation (AST parsing, world-readable MongoDB database, Big Table query to PyPI downloads). I'll additionally talk about some of the applications of this generalized library (coherent.build, pip-run), some of the maintenance challenges (expensive query, refresh interval), and possible other applications (on-demand dependency loader).

SPEAKER BIOS:

Alex C. Chang Alexander Chih-Chieh Chang is a fourth-year MSTP student in the CMU-Pitt Computational Biology Ph.D. Program, mentored by Drs. Lee and Oesterreich. He earned a BS/BA in Chemical and Biomolecular Engineering/Sociology from Johns Hopkins University in 2021. Previously, during his undergraduate research in the lab of Rong Li, Ph.D., he conducted large-scale genomic screens to study proteomic dysregulation and spent a gap year in the lab of Manish Aghi, MD. PhD., studying breast cancer metastasis to the brain. Currently, as a computational biologist and medical student, he coordinates the Hope for OTHERS tissue donation program in the Lee-Oesterreich Lab and computational research projects in breast cancer metastasis and genomic evolution. Brent Schlegel Brent Schlegel is a first-year PhD student in Integrative Systems Biology at the University of Pittsburgh School of Medicine, co-mentored by Drs. Adrian Lee and Steffi Oesterreich. He earned his AS in Mathematics and Sciences from CCAC (2019) and a BS in Computational Biology from Pitt (2021). Most recently, he worked as a Bioinformatics Analyst at the UPMC Children’s Hospital of Pittsburgh, where he specialized in the integrative analysis of large, complex biomedical datasets. Now, Brent combines data science, computational modeling, and multi-omic integration to tackle the systems biology of invasive lobular breast cancer, using patient-derived organoid models and leveraging “big data” to uncover hidden patterns and drive innovation in diagnosis and treatment.

Ling Almoubayyed Ling is an experienced architecture and urban designer with extensive project management expertise. Specializing in urban design, planning, community engagement, and spatial analysis, she has successfully led projects ranging from individual buildings to comprehensive urban districts. Ling uses evidence-based design with data gathered through stakeholder engagement to identify the best design solutions to create built environments. She is currently a Project Manager with SmithGroup. Husni Almoubayyed Husni Almoubayyed is the Director of AI at Pittsburgh-based education technology company Carnegie Learning. Husni uses machine learning and data science methods to conduct research in education, specifically in topics such as personalization, equity, and predictive analytics. Prior to his work in education technology, Husni acquired a Ph.D. in Astrophysics from Carnegie Mellon University, where he worked on mitigating biases in astronomical data to advance understanding of dark energy. Needless to say, Python is Husni's favorite programming language, and PyCon is one of his favorite events of the year!

Christopher Pitstick Christopher, a passionate software engineer who installed solar panels on his home in 2024, quickly immersed himself in system analysis to optimize performance—expertise that directly inspired this presentation. His programming journey began at age 12 with QBasic, igniting a lifelong passion that led to roles at industry giants including Microsoft, Amazon, and Argo AI before joining his current position at Latitude. Throughout his career, Christopher has mastered multiple programming languages from C++ to Perl and Python, approaching coding both as a profession and personal passion. As a dedicated neurodiversity advocate, he regularly shares his experiences through public speaking engagements, raising awareness and empowering others in the tech community.

Utkarsh Tripathi Utkarsh Tripathi is a Machine Learning Engineer at Solventum, Inc., where he works on Solventum™ Fluency Align™ and Solventum™ Fluency Direct™ : AI-powered clinical documentation tools that leverage conversational and generative AI, along with ambient intelligence, to automate medical documentation. These solutions help reduce administrative work and physician burnout, while improving the overall patient care experience. Utkarsh holds degrees in Electrical Engineering, Chemistry, and Computer Science from BITS Pilani and the University of Chicago.

Louis Luangkesorn Dr. Louis Luangkesorn is a Lead Data Scientist at Highmark Health where he works on projects applying statistical, predictive, operations research, and Generative AI models in use cases involving human resources and healthcare. He has contributed code to Scipy and a book appendix porting a simulation textbook's examples to Simpy.

Carolyn Tett Carolyn is an ecologist that specializes in animal behavior and disease ecology. She works with guppies and their ectoparasites to better understand how host contact rate and physiological status impact disease spread. She captures guppy behaviors on video and uses Python to automate the video processing. Using these outputs, she quantifies guppy social metrics and runs statistical models to predict behavior-mediated parasite spread.

Bryan C. Mills Bryan maintains Python core services at Duolingo, and was formerly a maintainer on the Go project at Google.

Jason R. Coombs Jason's been a passionate contributor to Python and open source software since the 90's, is a core contributor to Python, and maintains hundreds of packages in PyPI.

Register for the event to reserve your spot!

Date and Time Feb 7, 2025 from 5:30 PM to 8:30 PM

Location The Meetup will take place at MotionLab.Berlin, Bouchéstraße 12/Halle 20 in Berlin

Smart Data Loops: A New Paradigm for AI Development and Anomaly Detection

In the era of autonomous driving, the quality and efficiency of AI development hinge on the ability to manage data intelligently. This talk introduces the concept of Smart Data Loop, a novel paradigm that revolutionizes data handling by improving out-of-distribution detection, and leveraging trigger functions to refine AI models continuously. We will explore how these innovative approaches enhance anomaly detection and streamline AI workflows.

About the Speaker

Dr. Azarm Nowzad holds a PhD in Computer Science and serves as the Technical Project Lead and Product Owner for “Data for AI” at Continental Automotive. She is currently leading the publicly funded project “justbetterDATA”, which focuses on developing efficient and highly accurate data generation methods for AI applications, particularly in the field of autonomous driving. With her expertise in computer vision and AI, she plays a pivotal role in advancing data-driven solutions for next-generation mobility.

All About Agentic AI

Today, the concept of Agentic AI is shaping how we think about intelligent systems. These are AI systems designed to act autonomously, making decisions, completing tasks, and interacting with their environment—beyond traditional AI models. Understanding how to design and develop Agentic AI products is essential for staying ahead in the competitive landscape of AI-driven innovation. In this talk, Dr. Arman Nassirtoussi introduces Agentic AI. He’ll cover how these systems differ from standard AI, the evolving architectures that support them, and why they’re becoming critical.

About the Speaker

Dr. Arman Nassirtoussi earned his PhD in AI over a decade ago, focusing on predictive AI algorithms for intraday financial trading using Natural Language Processing (NLP), sentiment analysis, and text mining of online news. His main publication has quickly received over 1,200 citations on Google Scholar. Arman has led large data engineering, data science, and AI teams at companies like Henkel, Zalando, and T-Systems, helping build infrastructure, platforms, and products with a major focus on personalization and product analytics in e-commerce. Arman has also created a number of startups in multiple countries, and he is currently shaping a new one in the Agentic AI space.

Bridging Minds and Machines: Aligning Human Behavior and Machine Algorithm

As AI systems increasingly support human decision-making, integrating human-centered design principles into ML engineering has become essential. This talk bridges the foundational concepts of Human-Computer Interaction (HCI) with the complex demands of algorithmic decision-making, focusing on bidirectional Human-AI alignment, trust calibration, and Reciprocal Human-Machine Learning (RHML).

We explore the necessity of embedding human behavior and neurocognitive feedback loops into ML pipelines to enable adaptive and trustworthy systems. Addressing overtrust, undertrust, and trust miscalibration, we emphasize aligning ML systems with both high-performance metrics and user behavior, ensuring systems are effective and ethically aligned.

About the Speaker

Anke Borchers is an AI Strategist and Consultant specializing in Machine Learning (ML), Generative AI, and Trustworthy AI. With a background in Industrial and Communication Design and over 15 years of experience in innovation and business strategy, she bridges the gap between human-centered design and advanced AI systems.

Dedicated to crafting tailored solutions for the medical and business sectors, Anke highlights the critical importance of human-centered AI systems. She offers deep expertise in cognitive and machine decision-making, as well as AI Alignment, empowering organizations to develop AI solutions that are high-performing, ethically sound, and optimized to address user needs effectively.

Attention is All We Need: Using Transformers in Vision Tasks

Attention mechanism, initially developed for natural language processing, is now being effectively applied in Computer Vision. This talk will focus on how attention enables Visual Transformers to capture context and why they are overpowering the classical approaches to vision tasks.

About the Speaker

Kira Kravets is a Machine Learning engineer at Kertos, specializing in LLMs and the development of trustworthy AI systems. With experience in Computer Vision, particularly in the highly demanding medical field, she is passionate about building real-world AI applications with all the limitations and restrictions of production environments.

Join our complimentary Masterclass, "Take the Lead in Machine Learning Innovation" to master end-to-end ML project management using Google Cloud’s powerful tools.

Whether you’re new to machine learning or looking to elevate your project management skills, this Masterclass will give you practical strategies and insights to successfully navigate the complexities of ML implementation.

Register now to lead your team into the future with Google Cloud-powered ML expertise and learn the best practices and actionable insights to optimize your cloud environment.

Register for Free: - https://cutt.ly/te9cnKdH

Schedule: - Date: Tue, Feb 4, 2025 Time: 12:00 PM - 2:00 PM EST

What Will You Learn :- 1. How machine learning drives innovation across industries. 2. End-to-end project phases: feasibility, data prep, model training, evaluation, and deployment. 3. Assess data characteristics and manage biases that influence ML model quality. 4. Understand the critical roles and collaboration needed for ML project teams.

The Meetup will take place at Factory Campus, Gatherweg 69 Pioneer building, 4th Floor, Skyline conference room in Düsseldorf.

How Language and Foundation Models can Support Vision Tasks in the Context of Autonomous Driving

This presentation explores the integration of language and foundation models to enhance vision tasks in autonomous driving. By leveraging advanced AI techniques, we can improve scene understanding, and decision-making processes, e. g. to cover long-tail scenarios in driving situations.

About the Speaker

Jochen Schroeer is a Principal Architect – Mobility and Lead Architect AVOps (Autonomous Vehicle Operations) at Microsoft.

When Images Look Alike - Mastering Perceptual and Exact Deduplication

Explore techniques for detecting duplicate and similar images at scale, from neural network embeddings and efficient quantization to perceptual and cryptographic hashing. Learn practical approaches for dataset cleaning, with focus on balancing accuracy and computational costs for large-scale deduplication.

About the Speaker

Antonio Rueda-Toicen, an AI Engineer in Berlin, has extensive experience in deploying machine learning models and has taught over 300 professionals. Since 2019, he has organized the Berlin Computer Vision Group and, since 2024, the AI Maker Community at Hasso Plattner Institut (HPI). He specializes in computer vision, cloud technologies, and machine learning. Antonio is also a certified instructor of deep learning in Nvidia’s Deep Learning Institute.

How to Make the Best Self-Driving Dataset

AV/ADAS is one of the most advanced fields in Visual AI. However, getting your hands on a high quality dataset can be tough, let alone working with them to get a model to production. In this talk, I will show you the leading methods and tools to help visualize as well take these datasets to the next level. I will demonstrate how to clean and curate AV datasets as well as perform state of the art augmentations using diffusion models to create synthetic data that can empower the self driving car models of the future,

About the Speaker

Daniel Gural is a seasoned Machine Learning Engineer at Voxel51 with a strong passion for empowering Data Scientists and ML Engineers to unlock the full potential of their data.

Dataset Safari: Adventures from 2024's Top Computer Vision Conferences

Datasets are the lifeblood of machine learning, driving innovation and enabling breakthrough applications in computer vision and AI. This talk presents a curated exploration of the most compelling visual datasets unveiled at CVPR, ECCV, and NeurIPS 2024, with a unique twist – we’ll explore them live using FiftyOne, the open-source tool for dataset curation and analysis. Using FiftyOne’s powerful visualization and analysis capabilities, we’ll take a deep dive into these collections, examining their unique characteristics through interactive sessions. We’ll demonstrate how to:

• Analyze dataset distributions and potential biases
• Identify edge cases and interesting samples
• Compare similar samples across datasets
• Explore multi-modal annotations and complex label structures

Whether you’re a researcher, practitioner, or dataset enthusiast, this session will provide hands-on insights into both the datasets shaping our field and practical tools for dataset exploration. Join us for a live demonstration of how modern dataset analysis tools can unlock deeper understanding of the data driving AI forward.

About the Speaker

Harpreet Sahota is a hacker-in-residence and machine learning engineer with a passion for deep learning and generative AI. He’s got a deep interest in RAG, Agents, and Multimodal AI.

Masterclass to manage end-to-end ML projects using Google Cloud tools. Learn practical strategies to navigate ML implementation, including end-to-end project phases (feasibility, data prep, model training, evaluation, deployment); assess data characteristics and biases; and understand the roles and collaboration needed for ML project teams.

🌟 Session Overview 🌟

Session Name: The Shitposting AI - An Ironic Solution to Fruitless Online Debate Speaker: Markus Schuttler Session Description: More often than not, online discussion is tedious, toxic, and doesn't lead anywhere. It's a fruitless obligation that has controlled humans for far too long. Luckily, the Innovation Hacking Team found a solution: automation.

We trained an AI (GPT) on comment threads from the social media platforms with the worst discussion culture: Twitter and Reddit. Using this AI, we can now take the human entirely out of the loop and have an authentic, endless, AI-generated online discussion. Finally, humans can return to higher duties such as learning about the latest big data trends, while resting assured that the important topics of today's society are still being discussed in an authentic internet style. The discussion is brought back to the physical world by a group of talking robot heads that take turns presenting their arguments. For those preferring written discussion, the discussion is simultaneously carried out in a Telegram-esque group chat.

🚀 About Big Data and RPA 2024 🚀

Unlock the future of innovation and automation at Big Data & RPA Conference Europe 2024! 🌟 This unique event brings together the brightest minds in big data, machine learning, AI, and robotic process automation to explore cutting-edge solutions and trends shaping the tech landscape. Perfect for data engineers, analysts, RPA developers, and business leaders, the conference offers dual insights into the power of data-driven strategies and intelligent automation. 🚀 Gain practical knowledge on topics like hyperautomation, AI integration, advanced analytics, and workflow optimization while networking with global experts. Don’t miss this exclusive opportunity to expand your expertise and revolutionize your processes—all from the comfort of your home! 📊🤖✨

📅 Yearly Conferences: Curious about the evolution of QA? Check out our archive of past Big Data & RPA sessions. Watch the strategies and technologies evolve in our videos! 🚀 🔗 Find Other Years' Videos: 2023 Big Data Conference Europe https://www.youtube.com/playlist?list=PLqYhGsQ9iSEpb_oyAsg67PhpbrkCC59_g 2022 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEryAOjmvdiaXTfjCg5j3HhT 2021 Big Data Conference Europe Online https://www.youtube.com/playlist?list=PLqYhGsQ9iSEqHwbQoWEXEJALFLKVDRXiP

💡 Stay Connected & Updated 💡

Don’t miss out on any updates or upcoming event information from Big Data & RPA Conference Europe. Follow us on our social media channels and visit our website to stay in the loop!

🌐 Website: https://bigdataconference.eu/, https://rpaconference.eu/ 👤 Facebook: https://www.facebook.com/bigdataconf, https://www.facebook.com/rpaeurope/ 🐦 Twitter: @BigDataConfEU, @europe_rpa 🔗 LinkedIn: https://www.linkedin.com/company/73234449/admin/dashboard/, https://www.linkedin.com/company/75464753/admin/dashboard/ 🎥 YouTube: http://www.youtube.com/@DATAMINERLT

Hello everyone! Thanks to all who turned out for the last meet up which was absolutely HUGE. I hope you all enjoyed the talks, I certainly did. For the next event we have another stellar line up for you all to enjoy! 25-30 minute talks followed by an open Q&A. Drinks, networking and of course tons of pizza.. Look forward to seeing you all then!

Lydia Monnington \| Analytics Leader Advanced SQL: top tips for dealing with real world data

Level up your SQL knowledge to deliver results in real world situations.

• Joining on messy data, what can go wrong and how to avoid it.
• Window functions, what makes them great and an example of how to use them to create sessions.
• Arrays, why data engineers use them and how to access data stored in them easily.

About me In her role as Head of Analytics at Stuart Lydia identified the most important challenges for Stuart’s business and designed data driven solutions for them. Past projects include identifying the drivers of delivery costs and recommending cities for the business to expand into.

Lydia believes that charities should have access to the same data driven insights as businesses. Lydia is a director of the Stemettes, who inspire and support girls, young women and non-binary young people in STEM and is on the Scoping Committee for DataKind who help charities, local government, and social enterprises to use data science.

Having graduated with a 1st in Maths from Oxford University, Lydia has held data and analytics roles at Ocado, GHGSat, and Meta (Facebook). In these roles Lydia has designed and implemented experimentation processes, forecast company growth, planned a warehouse, defined customer segmentations, identified issues in stock control processes to reduce missing items by two thirds, and built a product from scratch, project managing and leading the data work.

Reyam Enad \| Lead Data Scientist @ EDF Energy Data Done Right: Essential Best Practice in Data Science

I'll be sharing our journey in restructuring the team and establishing technical best practices to ensure flawless project delivery. This process has been about refining our approach, aligning skills with goals, and implementing standards that drive quality and consistency across our work. Through these efforts, we're not only enhancing our productivity but also setting the stage for continuous improvement and excellence in every delivery.

About me As a Lead Data Scientist in the nuclear energy sector, I am committed to harnessing advanced data science and AI to drive meaningful innovation in a critical industry. With a Master’s in Artificial Intelligence and a background that includes practical experience in software engineering, I bring a well-rounded technical perspective to my work, from developing predictive models to exploring advanced machine learning algorithms. I lead a team of data scientists with a particular focus on Natural Language Processing (NLP) and Generative AI, where keeping up to date with rapid advancements in these technologies is essential to our success.

Beyond my professional work, I am passionate about championing diversity and inclusion within the tech sector. As a leader in partnerships for Women in Data, I work to broaden opportunities for women in the field, creating pathways to build skills, confidence, and careers in data science.

Please aim to arrive at 6pm. The talks will start around 6.30pm (give or take a few mins) and there will be pizza and refreshments as always on arrival :)

Look forward to seeing you all soon!

Our Second Manchester DevOps Society meetup event has arrived! We are delighted to be partnered with CreateFuture, who are kindly sponsoring our event.

The event is being held at Colony One Silk St, Ancoats, Manchester.

In this event, we will be hearing from two exciting speakers, featuring CreateFuture discussing about AI, using Langlow, and Benjamin Clark talking about data-driven terraform for developers and users respectively.

Format of the meetup event will be as follows:

6pm – 6:30pm - Networking on arrival coupled with pizza and drinks provided by CreateFuture. 6:30pm – 7pm – First speaker will take to the stage. 7pm – 7:10pm – Break for refreshments and networking 7:10pm – 7:40pm – Second speaker will take to the stage. 8pm onwards – Networking at event space and the Seven Bro7hers Beerhouse (5 mins walk from the venue)

We are delighted to welcome 2 speakers to our second Manchester event.

#1 – Ross Bamford – Principal Software Engineer @ CreateFuture

Ross Bamford is a Principal Software Engineer at CreateFuture with over twenty years in the software business. Having worked on multiple machine-learning projects in the past, Ross was an early adopter when the genAI revolution came, and has taken the lead on large, high-profile commercial genAI applications at CreateFuture, where he also helps lead the generative AI engineering community and evangelise the technology to anyone who’ll listen.

Title – AI For Everyone: Enabling non-engineers with Langflow

Ross will be giving run through of what Langflow is, how we as engineers can deploy and use it to bring our less-technical colleagues on the journey, real-world examples of things some of our folks have built, and he will touch on some war stories from a non-devops-expert deploying and operating the thing internally. He is hoping to work in some live demo / example usage too!

#2 – Benjamin Clark - DevOps Consultant

Ben begun work in the tech industry at 17, and over a decare later he has since founded and lead DevOps teams across multiple large organisations as both an employee and independent contractor. With a strong focus on elevating teams from just developing software to properly engineering software as a discipline, he believes strongly that the Software Development Lifecycle should apply across both Infrastructure and Application stacks.

Title - Data-driven Terraform for developers and users: Enabling self-service with a focus on readability and ease-of-use

Ben will be speaking about how Terraform with data structures and algorithms can drastically accelerate release cadence, enable developer self-service, and act as a foundational underpinning of best practice across an organisation!

P.S. Please provide full name and email address for access to the Colony event space.

Address: Colony One Silk St, Ancoats, Manchester M4 6LZ

Our sponsors - CreateFuture is a dynamic digital consultancy in the UK, formerly known as XDesign. They specialise in creating digital products that address complex challenges without relying on fixed frameworks or creating dependency. Their team includes experts in software engineering, cloud solutions, innovation, strategy, and design.

Please register now to book your spot!

Building and managing AI products comes with its own set of unique challenges. Especially when they are under intense scrutiny like mobile and home assistants have dealt with in recent years. From dealing with the unpredictable nature of machine learning models to ensuring that your product is both ethical and user-friendly, the path to success isn’t always clear. But how do you navigate these complexities and still deliver a product that meets business goals? What key steps can you take to align AI innovation with measurable outcomes and long-term success? Marily Nika is one of the world's leading thinkers on product management for artificial intelligence. At Google, she manages the generative AI product features for Google Assistant. Marily also founded AI Product Academy, where she runs a BootCamp on AI product management, and she teaches the subject on Maven. Previously, Marily was an AI Product Lead in Meta's Reality Labs, and the AI Product Lead for Google Glass. She is also an Executive Fellow at Harvard Business School. In the episode, Richie and Marily explore the unique challenges of AI product management, experimentation, ethical considerations in AI product management, collaboration, skills needed to succeed in AI product development, the career path to work in AI as a Product Manager, key metrics for AI products and much more.  Links Mentioned in the Show: Komo AIConnect with MarilyMarily’s Course: AI Product Management Bootcamp with CertificationSkill Track: AI Business FundamentalsRelated Episode: Building Human-Centered AI Experiences with Haris Butt, Head of Product Design at ClickUpRewatch sessions from RADAR: AI Edition New to DataCamp? Learn on the go using the DataCamp mobile appEmpower your business with world-class data and AI skills with DataCamp for business

PLEASE REGISTER HERE: https://meetup-september10.kickstartai-events.org

PyData Eindhoven & Kickstart.ai We are very happy to announce that we are organizing the next PyData Eindhoven meetup in collaboration with Kickstart.ai! We will host this meetup at the AI Innovation Center, located at the High Tech Campus in Eindhoven.

This meetup is set to take place on September 10, 2024, at the Al Innovation Center in the High Tech Campus, Eindhoven. Mark your calendar and join us for an evening of insights, networking, and cutting-edge technology! Learn the ins and outs of cutting-edge Al and machine learning with our expert speakers, Merel Theisen (Principal Software Engineer at QuantumBlack) and Emilio Oldenziel (Machine Learning Engineer at Eraneos). Discover how software engineering principles can elevate machine learning projects and how Al is optimizing rail traffic control through innovative solutions. Come and connect with fellow Al experts at our Cutting-Edge Al and Machine Learning Innovations meetup, where you'll have the chance to learn from top experts in the field and share your own experiences. Our events provide a platform for collaboration and knowledge sharing, helping us all to advance in the fast-evolving world of Al. And after an evening of learning, enjoy networking drinks and bites, where our speakers will be available to chat and answer any questions you have about Al and machine learning.

Program

• 17:30 – 18:00 Doors Open
• 18:00 – 18:10 🎤 Welcome
• 18:10 – 19:00 🎤 Merel Theisen Principal Software Engineer, QuantumBlack - Embedding Software Engineering Best Practices into Machine Learning Projects with Kedro
• 19:00 – 19:15 🍕 Food
• 19:15 – 20:00 🎤 Emilio Oldenziel Machine Learning Engineer, Eraneos - Optimizing Rail Traffic Control using a Digital Twin and Reinforcement Learning
• 20:00-21:00 🥤 Drinks
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Embedding Software Engineering Best Practices into Machine Learning Projects with Kedro In this talk, I will explore how software engineering best practices such as modularity, separation of concerns, testability, and reproducibility can elevate the quality and deployability of machine learning projects. Focusing on the Kedro framework, I’ll uncover how these principles integrate into data workflows, making complex projects more manageable and scalable. Attendees will gain practical insights into improving project design, ensuring code quality, and facilitating smoother transitions to production environments. No extensive software engineering background is required, making this an accessible and informative session for all data professionals looking to enhance their knowledge of software principles through Kedro. About I am a Principal Software Engineer at QuantumBlack, where I am currently the tech lead of Kedro, an open-source project part of the Linux Foundation. I have over eight years of experience in the software industry, with most of my career focused on backend product engineering. I am passionate about building products that solve real user problems, and I care deeply about creating robust, well-tested software that follows good engineering principles. I am also a strong advocate for open-source software, and I find working with the community to be both inspiring and energising.

---- Optimizing Rail Traffic Control using a Digital Twin and Reinforcement Learning In this talk, I will do a deep dive into one of our recent customer cases. In the customer’s railway network, train frequency is high, with trains departing every 3 minutes at some stations. Consequently, even a small disruption can affect the punctuality of many subsequent trains. Train dispatchers are tasked with resolving conflicts efficiently to minimize delays. I will discuss how a Digital Twin and using Reinforcement Learning (RL) can support dispatchers in making smarter decisions and the challenges of implementing RL solutions. I will demonstrate how combining scientific and practical RL knowledge reduced delays by over 58,000 minutes annually. About Emilio is an expert in the field of machine learning. At the Eraneos Data & AI practice he is responsible for advising on, developing and implementing AI solutions. He has a background in computing science and has worked on AI projects for companies like Porsche, Deutsche Bahn, Enexis and HTM. Transport and Logistics is one of his industry focuses, where he sees a lot of value in applying AI.

Join us at the Daemon Clubhouse on June 13th for an evening of talks, food, and conversation with ML and AI industry pros.

Please note you will be unable to enter the venue before 6.30pm.

RSVPs will close 24 hours before the event, you will be unable to register after this time but you can still watch online.

If you can't join us in person you can watch remotely via our YouTube channel.

Agenda

06:30pm - Doors open, food and drink served

07:00pm - Welcome

07:05pm - An opening statement from Daemon

07:10pm - Konrad Bachusz, Lead Data Engineer at Credera, "State of AI in 2024"

Konrad Bachusz has a broad range of experience in finance and data, working in various industries including accounting, government, trading, healthcare, transportation, finance, and consulting. Currently, he is a Lead Data Engineer at a global boutique consultancy called Credera. His current role involves helping enterprise clients deliver data engineering, data platforms, and AI solutions. Konrad's interest in AI stems from his background in data analytics, data science, machine learning and data engineering. Outside of work he enjoys travelling, playing his guitars and programming.

07:50pm - Break

08:00 - Lucy Thomas ML Engineer at the Natwest Group and Dr. Ariadna Blanca Romero Senior Data Scientist / AI-Machine Learning Engineer at the Natwest Group, "Enterprise Scale MLOps at NatWest"

Lucy and Ariadna will take us on NatWest Group's journey of building an MLOps platform that streamlines the entire machine learning lifecycle, and examples of using additional tools to support MLOps. This platform has boosted team productivity, reduced manual workflows for building, training, and deploying models, and enhanced security and compliance.

Lucy Thomas is a Senior AI/ML Engineer at NatWest Group, working in the Data Innovation team. Her focus at the moment is building ML solutions for conversational intelligence that are reliable and robust. Outside of work she enjoys going to the gym, swimming in the sea and reading.

Dr. Ariadna Blanca Romero is a Senior Data Scientist/AI-ML Engineer at NatWest with a background in computational material science. She is passionate about creating tools for automation that take advantage of the reproducibility of results from models and optimize the process to ensure prompt decision-making to deliver the best customer experience. Ariadna volunteers as a STEM virtual mentor for a non-profit organization helping the professional development of Latin-American students and young professionals, particularly for empowering women. She is passionate about practising yoga, cooking, and playing her electric guitar.

09:00pm - Wrap up, drinks at The Bear

Our hosts require that we provide a list of all attendees, please ensure that you register with a name that matches your government issued ID or bank card: if you do not we cannot guarantee you entry to the building.

Please RSVP for the event well in advance if you plan to attend in person and unRSVP if you can no longer attend as limited spaces are available.

Xcode/Swift/RealityKit or Unity/C#/PolySpatial?

If you are an app developer unsure about which approach to choose or simply want to learn about developing for the Apple Vision Pro, join our panel of experts (who have already successfully published apps on Apple VisionPro) in this live roundtable as they discuss the pros and cons of each workflow.

Attendees are welcome to ask questions and even contribute to the discussion. The panel will consist of senior developers who have used the tools and gathered insights through Apple Vision Pro sprints over the last few months.

Link to register:

https://www.eventbrite.com/e/the-developers-dilemma-unity-vs-swift-for-apple-vision-pro-development-tickets-896118373177?aff=meetup

Round table Takeaways

Decision-Making:

• Should I choose Xcode/Swift/RealityKit or Unity/C#/PolySpatial as a Unity or native developer?
• Which advantage/disadvantage does each option hold?
• The unique pitfalls and challenges associated with each pathway.

Our expert's opinion:

• What is the best way to bring an XR or mobile app to the Apple Vision Pro?
• Which approach makes the most sense for specific types of apps/games?
• How having a Windows, Volumes or Spaces app matters affects your decision.

The Pathway:

• How do I get started and publish apps/games with Unity/Polyspatial?
• How do I get started and publish apps/games with Swift/XCode/RealityKit?
• How long does it take to switch to Swift/Unity?

What's next:

• Special focus: Share Play and Multiplayer App Development for Apple Vision Pro
• Outlook: What to expect from WWDC 2024.

Speakers

James Ashley, Apple Vision Pro Lead Developer at Imaginative Universal James, with over a decade in spatial computing, computer vision, and machine learning, excels as a Principal XR Engineer at Project Archer, a pioneering AR startup under Walmart's innovation wing, Store No. 8. His expertise spans developing for advanced platforms like Apple Vision Pro, HoloLens 2, and Magic Leap 2. At Project Archer, he spearheaded the engineering for Walmart's Apple Vision Pro app, actively contributing from ideation to coding. James is also noted for his educational contributions to mixed reality development and his passion for enhancing user interfaces with AI.

I. Yosun Chang, Founder/CTO, AIMagical + Permute.xyz Permute.xyz is a AR+VR+CV+IoT+AI/ML+Cool Stuff startup studio founded by I. Yosun Chang, an AR industry veteran and visionary who has conceived and built MVP software that has won 2 TechCrunch Disrupt Grand Prizes, 3 Intel Perceptual Computing Challenge First Places, AT&T Shape Hackathon Grand Prize, Warner Brothers AT&T IoT Hackathon Grand Prize, Money2020 First Place,Launch Festival Best Buy First Place, PayPal NYC Hackathon Grand Prize, Dreamforce Hackathon, Microsoft Build, Amazon Alexa Hackathon, SXSW Music Hackathon and hundreds more. Most recently, her app DrawmaticAR became the first solo contribution to win SIGGRAPH Real-Time Live.

Details:

Our first Manchester DevOps Society event has arrived! We are delighted to be partnered with our hosts AccessPay, and our co-organisers Generative AI UK Community.

In this event, we will be hearing from Auto Trader and Microsoft. Format of the meetup event will be as follows: 6pm – 6:30pm - Networking on arrival coupled with pizza and drinks provided by ReVybe IT. 6:30pm – 6:55pm – First speaker will take to the stage to talk about Auto Trader’s journey from a traditional environment into the cloud. 6:55pm – 7:15pm – Break for refreshments and networking 7:15pm – 7:40pm – Second speaker will take to the stage to talk about Microsoft Azure’s AI services. 7:40pm – 8:30pm – Networking and event close. We are delighted to welcome 2 speakers to our first Manchester event. #1 – Dave Whyte – Operations Lead – Auto Trader Dave Whyte is the Operations Lead at Auto Trader UK, the premier digital automotive marketplace in the UK. With over two decades of experience, Dave has been instrumental in shaping the evolution of the IT Operations department, driving remarkable levels of stability, availability, and performance. His expertise lies in implementing robust support processes, harnessing the advantages of the Public Cloud, and fostering organizational agility to adapt to dynamic industry demands. Title – Auto Trader’s Journey to the Cloud Join us as we delve into Auto Trader's journey from a traditional environment to the cloud. We'll explore the pre-migration landscape, highlighting its constraints and challenges. Discover the compelling motivations that drove the transition to the cloud and gain valuable insights into the lessons gleaned throughout the transformation process. Finally, we'll glimpse the present-day landscape, showcasing the tangible outcomes of embracing cloud technology. #2 – Ethan Jones – Cloud Solutions Architect (AI) – Microsoft Ethan is a certified data scientist, community co-founder, and Microsoft advocate who has experience leading machine learning and data science projects for numerous FTSE 100 companies, from ideation to production. He is a rising star at Microsoft, who works with engineering teams and customers to accelerate adoption of their machine learning stack on Azure, driving digital transformation forwards to new heights. Title – Discussing how Microsoft utilise Azure AI Services Ethan will be speaking on how Microsoft utilise AI services within the Azure sphere, and how AI is driving digital transformation forward in businesses as machine learning and data science leads the charge on innovation in tech.

Dear members of the Criteo community,

Generative AI is revolutionising the way we design, create and interact with technology. The Criteo Tech Meet will be an immersive dive into this fascinating world, exploring the infinite possibilities offered by Generative AI.

For this edition, we are delighted to welcome our VP of Engineering on AI, who will introduce the event. We are also privileged to welcome three exceptional speakers, one from our R&D team and two guest speakers from Sicara.

Agenda

- 6:30 PM - Welcoming

- 7:00 PM -

• Introduction by our VP Engineering on AI ; Romain Lerallut
• Talk: Unleashing Creativity: The Magic of Generative AI by Jaspreet Kaur Sandhu, Machine Learning Engineer at Criteo. In this talk, we will delve into the captivating world of Generative AI, a cutting-edge technology that is transforming industries and captivating the imagination of both machine learning experts and the general public alike. Generative AI is a branch of artificial intelligence that focuses on the creation of content, including but not limited to audio, code, images, text, simulations and videos. We will dive deep into its history, fundamental building blocks, its potential to transform the creative process as we know it and the impact that will be felt across industries with an emphasis on advertising. We will further take a tour through some important questions that Generative AI has resurfaced, and which often are linked to its virality in news reports, like ethics, ownership, bias, whether creative ability implies consciousness and much more.
• Talk: Building LLM-based products: technical and product learnings by Pierre-Henri Cumenge, CTO & Noé Achache, Lead AI Engineer from Sicara. While building Proof of Concepts has become incredibly easy, building a product using LLMs that actually brings value to its users has its own challenges, especially in circumstances where we need high accuracy of the results. In this talk, we will explore the lessons learned from building two products that are typical use cases of these technologies: a financial document analysis automation and a RAG (retrieval augmented generation) tool for the drug documentation of a medical company. After detailing the product architectures, we will explore how we used other techniques on top of the LLMs to improve accuracy, how to improve the product UX to take into account imperfections of the models, and how to optimize the costs and performance when scaling past a proof of concept with GPT-4. We will dig as well into the tools, such as Langsmith, that helped us improve our datasets and helped the product experts assist the technical team in building these products.

- 8:30 PM - Networking and cocktails.

The event is open to all technology enthusiasts. Registration is free, but places are limited. Make sure you book yours now to guarantee your attendance on this unique day.

Don't miss this opportunity to dive into the future of Generative AI with Criteo. Together, we're shaping the face of technological innovation. The Criteotech meetups team. If you register for this event, you consent to CRITEO's use of your image, video, voice or all three. In addition, you waive any right to inspect or approve the finished video recording. You agree that any such image, video or audio recording and any reproduction thereof shall remain the property of the author and may be used by Criteo as it sees fit. You understand that this consent is perpetual, cannot be revoked by me and is binding. You understand that these images may appear publicly on Criteo's website, social media accounts and/or other marketing materials.

The Women in Machine Learning & Data Science (WiMLDS) Meetup aims to inspire, educate, regardless of gender, and support women and gender minorities in the field. We are back for our 46th edition, are you ready to get all the answers about data science?

All genders may attend our meetups.

Agenda

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19:00 - Launch of the evening by the Paris WiMLDS meetup team

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19:15 - Optimizing GenAI Applications: Evaluation in Retrieval-Augmented Generation by Nour El Mawass, GenAI's group Tech Lead & Maria Knorps, Senior Data Engineer @Tweag

Abstract: Nour and Maria present the work they did at Tweag, Modus Create innovation arm, where the GenAI team developed an evaluation framework for Retrieval-Augmented Generation (RAG) systems. RAG systems provide an easy and low-cost way to extend the knowledge of Large Language Models (LLMs) but measuring their performance is not an easy task. The presentation will review existing evaluation frameworks, ranging from those based on the traditional ML approach of using groundtruth datasets, including Tweag's, to those that use LLMs to compute evaluation metrics. It will also delve into the practical implementation of Tweag's chatbot over two distinct documents datasets and provide insights on chunking, embedding and how open source and commercial LLMs compare.

Twitter / X : *@*Nour_MS1 & *@*gemusia

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19:40 - Managing international tech teams by Natasha Dimban, Vice-Présidente Observatoire de la Fintech et Consultante

Abstract : Natasha will share her experience to delve into the complexities, challenges, and strategies associated with effectively leading tech teams dispersed across borders

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20:05 - Perspectives by Morgane Pannegeon, Acculturation Officer @Société Générale

Abstract : Morgane will take us through a personal journey : going back to school when you are between 40 and 50 years old and falling in love with R.

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20:45 - Cocktail with meetup participants

During the event, you can share content using @WiMLDS_Paris.

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Host information : coming soon! It will be in central Paris, next to Opéra Garnier.

After the meet-up, all the slides will be available on our Medium page : https://medium.com/@WiMLDS_Paris

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Codes of Conduct

WiMLDS is dedicated to providing a harassment-free experience for everyone. We do not tolerate harassment of participants in any form. All communication should be appropriate for a professional audience including people of many different backgrounds. Sexual language and imagery is not appropriate.

Be kind to others. Do not insult or put down others. Behave professionally. Remember that harassment and sexist, racist, or exclusionary jokes are not appropriate.

Thank you for helping make this a welcoming, friendly community for all. All attendees should read the full Code of Conduct before participating: https://github.com/WiMLDS/starter-kit/wiki/Code-of-conduct