On-Demand Learning

Explore our catalogue of recorded demos, webinars, and events to get a deeper understanding of Seldon and help you along your MLOps journey.

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MOST RECENT

Agentic LLM Reasoning at Scale

In this session, Alex Housley introduces the advancements in Deepseek V3, focusing on the integration of LLMs within a data-centric MLOps framework. 

LLM Loan Processing Pipeline​

This demo showcases how to build a production-ready pipeline combining an LLM (Mistral) with traditional ML (Random Forest) for automated loan approval. It includes setting up manifests, deploying models and preprocessors, and making inference requests with outputs in structured JSON.

DeepSeek Reasoning Cake Mystery

This demo evaluates DeepSeek’s reasoning ability by solving a structured riddle about a missing birthday cake. It highlights how context window size affects LLM reasoning and includes code walkthroughs for analyzing outputs with reasoning vs. answer breakdowns.

DeepSeek R1 (14B) Vanishing Ambassador Mystery​

This demo attempts to run a more complex prompt requiring deep reasoning with a larger model (14B parameters). Though it runs into errors with context window configuration and prompt formatting, it serves as a stress test for multi-GPU loading and memory handling.

MLOps London

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Our meetups offer a space to share insights, learn, and hear from industry leaders on tools, challenges, and best practices.

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Explore Previous Webinars

Building Data-Centric Machine Learning at Scale with Seldon Core 2

This webinar covers: 

  • The methodology behind Core 2 and its purpose-built design for data-centric ML challenges.

  • A demo detailing how Core 2 promotes data-centricity including building modular ML applications and monitoring those systems in production

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How to make ML Model Experimentation Easier with Seldon

This session explores how to effectively test and deploy ML models using Seldon Core, covering:

  • ML Experimentation Strategies: A/B testing, canary deployments, and shadow mode testing for safe and controlled model rollouts.
  • Overcoming Deployment Challenges: Handling model routing, scaling, versioning, and performance tracking to ensure smooth experimentation.
  • Demo walkthrough: Setting up experiments in Seldon Core, plus insights on advanced use cases like sticky sessions and model-specific routing. 
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The EU AI Act: What MLOps Teams Need to Know

In this session, we break down the key aspects of the EU AI Act, including:

  • EU AI Act Overview & Risk Categories: Understanding prohibited, high-risk, and limited-risk AI classifications, along with compliance obligations for providers and deployers.
  • Regulatory Timelines & Compliance Readiness: Key deadlines for AI legislation enforcement and practical steps to prepare, including post-market monitoring requirements.
  • Seldon’s Approach to Compliance: How Seldon’s data-centric architecture, model versioning, explainability, and monitoring tools support compliance with AI risk management and regulatory frameworks.
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