San Diego’s AI Meetup Builds Community Through Learning & Collaboration

Artificial intelligence might be shaping the future of business, but in San Diego, it’s also building something else: community.

At the heart of this movement is the San Diego Machine Learning Meetup, a grassroots group of AI enthusiasts, students, and professionals co-led by Ryan Chesler, a self-taught data scientist and Kaggle 2x Grandmaster. Every Saturday at noon, this group gathers—online and in person—to learn, share, and grow together in one of the fastest-moving fields in tech.

We sat down with Ryan for an episode of our Driving Tomorrow interview series to learn more about the group’s origins, goals, and future plans. Spoiler: It started by accident.

“The guy who originally ran the group had it set to auto-schedule every week… and eventually, he just stopped showing up,” Ryan laughed. “I kept going, and when his auto-schedule ran out, I started my own. It wasn’t by design—it was just inherited.”

Since then, Ryan and his co-organizer, Ted, have turned the group into a learning hub for the region, offering something for everyone—from complete beginners to seasoned practitioners.

Meeting People Where They Are

One of the group’s greatest strengths is its ability to support people at different stages in their learning journey.

“Obviously someone who’s very experienced has different interests than someone just dipping their toe into the field,” Ryan explained. “So we have different events that are catered to different people—like beginner-friendly book clubs, and more advanced academic paper discussions.”

Recently, the group has been piloting interactive case study sessions where members work through real-world machine learning challenges together in small groups. According to Ryan, it’s the most impactful thing they’ve done yet.

“You can read a book on your own,” he said. “But actually interacting with the group, learning from each other, and hearing new perspectives—that’s something you can’t get anywhere else.”

Attendee Takeaways: From Research Methods to Real-World Insight

For attendees like Juan Torres, a Research & Data Analyst, these case studies bridge theory and practice.

“It made a clear connection between the research methodology and the machine learning methodology to solve issues. See, the real take here is the research methodology (developing good research questions, problem statements, etc.) is functional across all fields of strategic/scientific/research fields,” he said. “As complex as ML modeling can be, the principle of the Path of Least Resistance still applies. That was my greatest takeaway.”

Anastasiya Kuznetsova, a postdoctoral fellow at Scripps Research, echoed that insight from a life sciences perspective.

“The event emphasized the importance of carefully selecting a model according to the task rather than defaulting to deep learning,” she noted. “Many tend to build complex models from scratch without considering constraints like computational resources, time, and effort. It learned the value of focusing on the task first and going step-by-step—starting with a simple approach before introducing complexity”

Building Confidence and Community

While the learning is valuable, Ryan believes it’s the connections people make that keep them coming back.

“The biggest indicator of success isn’t how much they learned—it’s whether they talked to someone else at the event,” he said. “That’s how people build the habit of learning and start seeing themselves as part of this community.”

For many, showing up regularly to events—even if they’re not expert coders—becomes a gateway into the AI field.

“It’s very important,” Ryan said. “You can be brilliant, but you still need to communicate your ideas. Presenting to the group helps people flex a muscle most don’t use very often.”

🎥 Want to hear more from Ryan Chesler?
Watch the full interview below to hear how he got started, what makes San Diego’s ML Meetup unique, and why showing up matters more than being an expert.

Laying the Groundwork for an AI Hub

As AiNews.com continues its mission to help make San Diego a leading AI hub, community groups like San Diego Machine Learning are laying the foundation.

“We’re focused on building skills from the ground up,” Ryan said. “We’re not pushing people to start companies—we’re helping people build the capabilities to eventually collaborate on cool projects.”

That kind of grassroots strength, Ryan believes, is essential for long-term growth.

Looking Ahead: From Pilot to Platform

The future of the group is centered on expanding the case study program. Ryan and Ted are working on refining the format to make it even more effective for skill-building and problem solving.

“We want to get the best-case studies possible—ones that really stretch people’s thinking,” Ryan said. “Because in the end, problem solving is the skill that endures across tools, trends, and technologies.”

Interested in Joining?

The San Diego Machine Learning Meetup meets every Saturday at noon, and events are posted on their Meetup page. Whether you’re just starting out or deep into your AI journey, you’ll find thoughtful discussions, new challenges, and a welcoming community.

“It’s not too late to learn and jump in,” Ryan said. “Just start. There’s no wrong path—as long as you keep going.”

Start your machine learning journey here: San Diego Machine Learning Meetup.

Editor’s Note: This article was created by Alicia Shapiro, CMO of AiNews.com, with writing, image, and idea-generation support from ChatGPT, an AI assistant. However, the final perspective and editorial choices are solely Alicia Shapiro’s. Special thanks to ChatGPT for assistance with research and editorial support in crafting this article.