Machine Learning
Events
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Weekly paper review, coding project, or random discussion
Online event***Please Use Source Link Below to Confirm Event Details*** This is a placeholder for our weekly meeting. We will update the meeting description each week to include the topic of the week. Stay tuned :) Every week we meet (virtually) and discuss the most interesting topics in AI, ML and Deep Learning. We usually rotate weeks so that every other week one of the members presents a deep learning/machine learning paper, frequently paired with a video explaining the concepts. In the off weeks, we present information about different projects. We cover computer vision, language (LLM's), health/hard science and generative models (Diffusion, GAN's etc.). People of all levels of skill are welcome--from newbies to machine learning, to PhD's in DL/ML/AI. We have been meeting for over 6 years weekly and have developed a neat pace and community--and all are welcome. Come join us and stay abreast of the biggest topics in Artificial Intelligence. Original Event: Weekly paper review, coding project, or random discussion
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Generative AI Paper Reading
Online event***Please Use Source Link Below to Confirm Event Details*** Every second week we meet to discuss machine learning papers. This is a collaboration between Silicon Valley Generative AI and Boulder Data Science. Original Event: Generative AI Paper Reading
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Conf42 Internet of Things (IoT) 2025
Online event***Please Use Source Link Below to Confirm Event Details*** Join the Community for the Conf42 Internet of Things (IoT) 2025 event. The event will cover topics in Robotics, Artificial Intelligence, and Machine Learning. Original Event: Conf42 Internet of Things (IoT) 2025
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Community Lightning Talks
Online event***Please Use Source Link Below to Confirm Event Details*** Our January Meetup will be a remote gathering; the Zoom link will be posted the week of the event. Continuing our regular tradition, our first meeting of 2026 will be a collection of lightning talks presented by members of our community like YOU. From successes to failures and from beginner to advanced, we want to hear about your R experience. Talks are expected to be 5-7 minutes, not highly polished, and presented in rapid-fire succession. We'd love to hear your perspective! The meeting will be virtual and open to all; speakers from the local SLC community will be given preference for spots. Original Event: Community Lightning Talks
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Artificial Intelligence and Machine Learning Weekly: Learn, Build, Connect
Online event***Please Use Source Link Below to Confirm Event Details*** Join us every week for a hands-on, engaging session where we dive into the fascinating world of Artificial Intelligence and Machine Learning — from the basics to cutting-edge developments like Agentic AI, Generative AI, and LLMs. Whether you're just getting started or already working on AI/ML projects, this meetup is for you. We’ll explore practical topics, walk through code together, showcase real-world use cases, and collaborate as a learning community. Original Event: Artificial Intelligence and Machine Learning Weekly: Learn, Build, Connect
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Artificial Intelligence and Machine Learning Weekly: Learn, Build, Connect
Online event***Please Use Source Link Below to Confirm Event Details*** Join us every week for a hands-on, engaging session where we dive into the fascinating world of Artificial Intelligence and Machine Learning — from the basics to cutting-edge developments like Agentic AI, Generative AI, and LLMs. Whether you're just getting started or already working on AI/ML projects, this meetup is for you. We’ll explore practical topics, walk through code together, showcase real-world use cases, and collaborate as a learning community. Original Event: Artificial Intelligence and Machine Learning Weekly: Learn, Build, Connect
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AI Application Development Program Info Session
***Please Use Source Link Below to Confirm Event Details*** Lead Innovation as a Machine Learning Engineer. As AI becomes central to products and services across industries, there’s a growing demand for professionals who can design, build and deploy intelligent services & systems. Learn how you can preprocess data, develop Machine Learning models, apply Deep Learning techniques, and create AI solutions that solve real‑world problems. Join Praveen Krishna, chair of the Artificial Intelligence Application Development program, for an inside look at how our courses provide hands‑on experience, industry‑driven projects, and the technical foundation you need to advance your career as an ML Engineer, MLOps Engineer, or Applied AI Researcher. Original Event: AI Application Development Program Info Session
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Designing Data Infrastructures for Multimodal Mobility Datasets
Online event***Please Use Source Link Below to Confirm Event Details*** This technical workshop focuses on the data infrastructure required to build and maintain production-grade mobility datasets at fleet scale. We will examine how to structure storage, metadata, access patterns, and quality controls so that mobility teams can treat perception datasets as first-class, versioned “infrastructure” assets. The session will walk through how to design a mobility data stack that connects object storage, labeling systems, simulation environments, and experiment tracking into a coherent, auditable pipeline. Original Event: Designing Data Infrastructures for Multimodal Mobility Datasets
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Teaching Computers to Read: Dataset Curation Impact on Model Performance
Online event***Please Use Source Link Below to Confirm Event Details*** Workshop Summary: Successful AI solutions aren’t about chasing the newest model - it’s about solving the right problems in the right way. The book “Teaching Computers to Read” (out November 5 from CRC Press) focuses on what technical teams need to design, develop, deploy, and maintain useful NLP and AI solutions. Drawing on real-world experience and examples, the book offers actionable best practices to deliver adaptable, reliable AI systems that address business challenges with lasting, tangible value. In this tutorial, we will walk through one part of the Code Companion for the book. We will review the corpus distribution and variation, our annotated data distribution, and explore how our curated datasets impact the performance of different technical approaches, using information extraction as an example. The concepts covered in the tutorial are covered in more detail in the book, and there are additional exercises in the Code Companion for those interested in going beyond the tutorial session. Original Event: Teaching Computers to Read: Dataset Curation Impact on Model Performance
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