ML Platform Podcast

ML Platform Podcast

By neptune.aiTechnology
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ML Platform Podcast episodes

  • Navigating Vector Databases: Indexing Strategies, GPU, and More
    Find the episode on our Youtube channel

    Resources:

    ImageBind: Holistic AI learning across six modalities
    Frank’s Liu website
    Milvus
    OSS Chat
    Follow us & stay updated:
    ► Visit our website
    ► Follow us on Linkedin
    ► Check our Github
    ► Follow us on Twitter

    Connect with Piotr on Linkedin
    Connect with Aurimas on Linkedin
    Connect with Frank on Linkedin
    Connect with Frank on Twitter/X

    The episode was recorded on 7 September 2023, and some information may not be up-to-date.

    Brought to you by neptune.ai
    1 hr 12 min
  • Learnings From Building the ML Platform at DoorDash With Hien Luu
    Find the episode on our Youtube channel

    Resources:

    Building a Machine Learning Platform [Definitive Guide]
    DoorDash’s ML Platform – The Beginning
    3 Principles for Building an ML Platform That Will Sustain Hypergrowth
    Hien's LinkedIn Survey

    Follow us & stay updated:
    ► Visit our website
    ► Follow us on Linkedin
    ► Check our Github
    ► Follow us on Twitter

    Connect with Piotr on Linkedin
    Connect with Aurimas on Linkedin
    Connect with Hien on Linkedin

    Brought to you by neptune.ai
    1 hr 7 min
  • Breaking Down Workflow Orchestration and Pipeline Authoring in MLOps
    Find the episode on our YouTube channel

    Resources:

    ZenML's big announcement
    ZenML on Github
    ML Experiment Tracking: What It Is, Why It Matters, and How to Implement It
    Follow us & stay updated:
    ► Visit our website
    ► Follow us on Linkedin
    ► Check our Github
    ► Follow us on Twitter

    Connect with Piotr on Linkedin
    Connect with Aurimas on Linkedin
    Connect with Adam on Linkedin
    Connect with Hamza on Linkedin

    Brought to you by neptune.ai
    53 min
  • Going Deep On Model Serving, Deploying LLMs and Anything Production-Deployment
    Find the episode on our YouTube channel

    The episode was recorded on 20 July 2023, and some information may not be up-to-date. Stay tuned for an updated version on our blog

    Resources:

    BentoML
    BentoCloud
    Learnings From Building the ML Platform at Uber (Michelangelo)
    Building a Machine Learning Platform [Definitive Guide]

    Follow us & stay updated:
    ► Visit our website
    ► Follow us on Linkedin
    ► Check our Github
    ► Follow us on Twitter

    Connect with Piotr on Linkedin
    Connect with Aurimas on Linkedin
    Connect with Chaoyu on Linkedin

    Brought to you by neptune.ai
    43 min
  • Building Internal ML Platform at Scout24: How to Ship Features that People Actually Need
    Find the episode on our YouTube channel

    Resources:

    The Long Tail: Why the Future of Business is Selling Less of More by Chris Anderson
    What Customers Want: Using Outcome-Driven Innovation to Create Breakthrough Products and Services by Anthony Ulwick
    The GitLab Handbook
    Building a Machine Learning Platform [Definitive Guide]
    Follow us & stay updated:
    ► Visit our website
    ► Follow us on Linkedin
    ► Check our Github
    ► Follow us on Twitter

    Connect with Piotr on Linkedin
    Connect with Aurimas on Linkedin
    Connect with Olalekan on Linkedin

    Brought to you by neptune.ai
    50 min
  • Building ML Platform at Uber, Feature Stores, Vector Databases, and Real-time Feature Management
    Find the episode on our YouTube channel

    Resources:
    Machine Learning: The High Interest Credit Card of Technical Debt
    Meet Michelangelo: Uber’s Machine Learning Platform
    Feature Stores and LLMs
    Building a Machine Learning Platform [Definitive Guide]

    Follow us & stay updated:
    ► Follow us on Linkedin
    ► Check our Github
    ► Join our Slack MLOps Community (#neptune-ai)

    Connect with Piotr on Linkedin
    Connect with Aurimas on Linkedin
    Connect with Mike on Linkedin

    Brought to you by neptune.ai
    1 hr 17 min
  • Year in Review: LLMs & LLMOps, State of MLOps, and What's Next in 2024
    On this special, end-of-the-year episode of the ML Platform Podcast, Piotr Niedzwiedzi and Aurimas Griciūnas discuss the state of MLOps and LLMOps, the impact of LLMs on layoffs and ML team composition, unsolved LLM challenges, use cases that don’t align with LLMs, MLOps and LLMOps predictions for 2024, and more.

    With LLMs and AI being the center of discussion we also decided to experiment with generative AI for this video. Hope you don’t mind the experimentation.

    Find the episode on our YouTube channel

    Resources:
    • MLOps is an extension of DevOps. Not a fork 
    • ML Platform Teams, Features Stores, and Where MLOps Extends DevOps With Aurimas Griciunas
    • Learnings From Building the ML Platform at Mailchimp With Mikiko Bazeley
    • The state of applied ML by Tecton
    • MLOps in 2023 by ClearML

    Follow us & stay updated:
    ► Follow us on Linkedin
    ► Check our Github
    ► Join our Slack MLOps Community (#neptune-ai)

    Connect with Piotr on Linkedin
    Connect with Aurimas on LinkedinBrought to you by neptune.ai
    1 hr 1 min
  • Building MLOps Capabilities at GitLab As a One-Person ML Platform Team With Eduardo Bonet
    Find the episode on our YouTube channel or read the podcast transcript

    Resources:
    MLOps Is an Extension of DevOps. Not a Fork
    The GitLab Handbook

    Follow us & stay updated:
    ► Follow us on Linkedin
    ► Check our Github
    ► Join our Slack MLOps Community (#neptune-ai)

    Connect with Piotr on Linkedin
    Connect with Aurimas on Linkedin
    Connect with Eduardo on Linkedin
    Brought to you by neptune.ai
    1 hr 4 min

About ML Platform Podcast

From the publisher's feed

Get behind-the-scenes insights into the world of internal ML platforms and MLOps stack components with Piotr Niedźwiedź and Aurimas Griciūnas in their show, where together with ML platform professionals, they discuss design choices, best practices, and real-world solutions to MLOps challenges.