What we're about

We’re excited to bring you the latest and practical technology on AI, Machine Learning, Deep Learning, Data Science and Big Data.

Our goal is to congregate with AI enthusiasts from all over Austin to learn and practice AI tech, through tech talks, study jams, code labs etc.. we regularly invite tech leads from innovated companies, successful startups to share their practice experiences and practices in the world of AI, Cloud, Data, Blockchain.

If you’d like to speak at future meetups, co-promote your meetup or inquire about partnership opportunities, please feel free to reach out to us.

Upcoming events (2)

ML Talk: Reasonable Scale Machine Learning

Link visible for attendees

Please complete registration on the event website to receive join link:
https://www.aicamp.ai/event/eventdetails/W2022053116

Description:
Machine learning comes in many shapes and sizes but most of the conversation (around tools, techniques, division of labor) is dominated by a handful of companies, who do ML at a scale nobody else needs to. Of all the endless forms that companies outside of Big Tech can take, particularly interesting is a growing and underserved segment that is especially relevant for ML systems, known as reasonable scale companies, meaning reasonable along the axes of monetary impact, team size, data volume, and compute resources.

Jacopo and Hugo will discuss reasonable scale machine learning and what the majority of non-FAANG companies need to know in order to build out sophisticated ML functions, and we will also discuss what such machine learning actually looks like for businesses and practitioners alike, and what you can do to get started with reasonable scale ML today.

After attending, you’ll know:

  • What types of companies can benefit from reasonable scale machine learning (hint: most);
  • What types of data, tools, and talent you need in order to build a sustainable ML function;
  • Barriers to entry for reasonable scale machine learning, how you can get started today, and industry trends that will help you in your ML journey.

The fireside chat will be followed by an AMA with Jacopo and Hugo at slack.outerbounds.co.

Speakers:
Jacopo Tagliabue is Coveo's Director of A.I., where they combine product thinking and research-like curiosity to build better data-driven systems at scale.
Hugo Bowne-Anderson, Outerbounds’ Head of Developer Relations

More AI/ML/Data tech events (free to join from anywhere):
🔷 May 17, Workshop: Hands-on NLP workshop
🔷 May 19, Webinar: Deliver Self-Service BI at Enterprise-Scale
🔷 May 24, Webinar: Redefining MLOps with Automated Model Monitoring in Production
🔷 May 24, Conference: Chief Data & Analytics Officers, Insurance
🔷 Jun 2, Webinar: Streaming data with Elasticsearch and Kafka
🔷 Jun 7, Webinar: Zookeeper vs Raft: Stateful Distributed Coordination with High Availability

Data talk: Insourcing vs Outsourcing Data Layer Operations

Link visible for attendees

Register on the event website to receive joining link: https://www.aicamp.ai/event/eventdetails/W2022060210

We are hosting a series of tech talks on Kafka, data layers, you can join us online from anywhere:

  • June 16: Using Free And Open-Source Software Vs. Open-Core Software.
    RSVP: https://www.aicamp.ai/event/eventdetails/W2022061610
  • June 29: Workshop: Migrating from Confluent Kafka to Open Source Apache Kafka.
    RSVP: https://www.aicamp.ai/event/eventdetails/W2022062910
  • July 14: PostgreSQL Enterprise Features.
    RSVP: https://www.aicamp.ai/event/eventdetails/W2022071410

Description:
Data layer management is one of the key things that impact the ability of developers to do their jobs. And knowing the right approach for your team, along with your company, will have major effects in both the short and long term. Selecting the right one for the right reasons is important to achieve the goals you have.

What will you get out of this webinar?
In this webinar we will go over the pros and cons of Insourcing vs Outsourcing Data Layer management with regards to things such as expertise, cost, resilience, and growth for both approaches.

Who should attend?
This webinar is intended for developers looking to understand the benefits and when it is best to outsource the management of their data layer.

More AI/ML/Data tech events up coming (free join from anywhere):
🔷 May 25, Webinar: Advanced Analytics & Insights More Actionable
🔷 Jun 7, Webinar: Zookeeper vs Raft: Stateful Distributed Coordination
🔷 Jun 7, Webinar: Built a Data Mesh Architecture
🔷 Jun 15, Conference: MLOps Summit (San Francisco)
🔷 Jun 16, Workshop: Build End-to-End Deep Learning Models
🔷 Jun 20, Webinar: Run Spark In Large Scale On Kubernetes
🔷 Jun 29, Workshop: Migrating from Confluent Kafka to Apache Kafka

Past events (253)

ML Talk: MLOps with Model Deployment and Observability in Production

This event has passed

Photos (216)