25 episodes

A podcast from DagsHub about bringing machine learning into the real world. Each episode features a conversation with top data science and machine learning practitioners, who'll share their thoughts, best practices, and tips for promoting machine learning to production

The MLOps Podcast Dean Pleban @ DagsHub

    • Technology
    • 5.0 • 1 Rating

A podcast from DagsHub about bringing machine learning into the real world. Each episode features a conversation with top data science and machine learning practitioners, who'll share their thoughts, best practices, and tips for promoting machine learning to production

    🩻 AI in Medical Devices & Medicine with Mila Orlovsky

    🩻 AI in Medical Devices & Medicine with Mila Orlovsky

    In this episode, I had the pleasure of speaking with Mila Orlovsky, a pioneer in medical AI. We delve into practical applications, overcoming data challenges, and the intricacies of developing AI tools that meet regulatory standards. Mila discusses her experiences with predictive analytics in patient care, offering tips on navigating the complexities of AI implementation in medical environments. This episode is packed with actionable advice and forward-thinking strategies, making it essential listening for professionals looking to impact healthcare through AI.

    Join our Discord community: https://discord.gg/tEYvqxwhah

    ---
    Timestamps:
    00:00 Introduction and Background
    4:03 Early Days of Machine Learning in Medicine
    5:19 Challenges in Building Medical AI Systems
    6:54 Differences Between Medical ML and Other ML Domains
    15:36 Unique Challenges of Medical Data in ML
    24:01 Counterintuitive Learnings on the Business Side
    28:07 Impact and Value of ML Models in Medicine
    29:41 The Role of Doctors in the Age of AI
    38:44 Explainability in Medical ML
    44:31 The FDA and Compliance in Medical ML
    48:56 Feedback and Iteration in Medical ML
    52:25 Predictions for the Future of ML and AI
    53:59 Controversial Predictions in the Field of ML
    56:02 Recommendations
    57:58 Conclusion

    ➡️ Mila Orlovsky on LinkedIn – https://www.linkedin.com/in/milaorlovsky/
    🩺MeDS – Medical Data Science Israel Community – https://www.facebook.com/groups/452832939966464/


    🌐 Check Out Our Website! https://dagshub.com

    Social Links:
    ➡️ LinkedIn: https://www.linkedin.com/company/dagshub
    ➡️ Twitter: https://twitter.com/TheRealDAGsHub
    ➡️ Dean Pleban: https://twitter.com/DeanPlbn

    • 58 min
    ⏪ Making LLMs Backwards Compatible with Jason Liu

    ⏪ Making LLMs Backwards Compatible with Jason Liu

    In this episode, I had the pleasure of speaking with Jason Liu, an applied AI consultant and the creator of Instructor – an open-source tool for extracting structured data from LLM outputs. We chat about LLM applications, their challenges, and how to overcome them. We also dive into Instructor, making LLMs interact with existing systems and a bunch of other cool things.

    Join our Discord community: https://discord.gg/tEYvqxwhah


    ➡️ Jason Liu on Twitter – https://twitter.com/jxnlco
    🤖 Instructor Blog – https://jxnl.github.io/instructor/

    🌐 Check Out Our Website! https://dagshub.com

    Social Links:
    ➡️ LinkedIn: https://www.linkedin.com/company/dagshub
    ➡️ Twitter: https://twitter.com/TheRealDAGsHub
    ➡️ Dean Pleban: https://twitter.com/DeanPlbn


    Timestamps:
    00:00 Introduction
    02:18 Excitement about Machine Learning and AI
    03:28 Using LLMs as Backend Developers
    04:22 Building Applications with LLMs
    07:07 Building Instructor
    09:30 Thinking in Logic and Design
    10:33 Validating Data and Building Systems with Instructor
    11:49 Thoughts About Product and UX in LLMs
    17:51 Future of Instructor
    20:25 Misconceptions and Unsolved Problems in LLMs
    24:57 Improving LLM Applications
    26:14 RAG as Recommendation Systems
    29:32 Fine-tuning Embedding Models
    32:32 Beyond Vector Similarity in RAG
    39:32 Predictions for the Next Year in AI and ML
    45:26 Measuring Impact on Business Outcomes
    47:06 The Continuous Cycle of Machine Learning
    48:38 Unlocking Economic Value through Structured Data Extraction
    50:52 Questioning the Status Quo and Making an Impact

    • 53 min
    🔴 Live MLOps Podcast – Building, Deploying and Monitoring Large Language Models with Jinen Setpal

    🔴 Live MLOps Podcast – Building, Deploying and Monitoring Large Language Models with Jinen Setpal

    In this live episode, I'm speaking with Jinen Setpal, ML Engineer at DagsHub about actually building, deploying, and monitoring large language model applications.

    We discuss DPT, a chatbot project that is live in production on the DagsHub Discord server and helps answer support questions and the process and challenges involved in building it. We dive into evaluation methods, ways to reduce hallucinations and much more.

    We also answer the audience's great questions.

    • 1 hr 11 min
    Live MLOps Podcast Episode!

    Live MLOps Podcast Episode!

    Join now to take part in our first live MLOps Podcast episode.

    I'll be chatting with Jinen Setpal, ML Engineer at DagsHub about his work building LLM applications and getting LLMs into production.



    Sign up for the event at the link here:

    https://www.linkedin.com/events/7098968036782596096/comments/

    • 28 sec
    ⛹️‍♂️ Large Scale Video ML at WSC Sports with Yuval Gabay

    ⛹️‍♂️ Large Scale Video ML at WSC Sports with Yuval Gabay

    In this episode, I had the pleasure of speaking with Yuval Gabay, MLOps Engineer at WSC Sports. Yuval builds better infrastructure and automation for developing, training, and deploying machine learning models at scale, with a focus on video data. We talk about MLOps methodologies, standardizing deployment in the organization, and closing the loop back from production into training.



    Watch the video: https://youtu.be/3m__nRuifsQ

    Join our Discord community: https://discord.gg/tEYvqxwhah


    ➡️ Yuval Gabbay on LinkedIn – https://www.linkedin.com/in/yuval-gabay-68963253/
    ➡️ WSC Sports – https://wsc-sports.com/

    🌐 Check Out Our Website! https://dagshub.com

    Social Links:
    ➡️ LinkedIn: https://www.linkedin.com/company/dagshub
    ➡️ Twitter: https://twitter.com/TheRealDAGsHub
    ➡️ Dean Pleban: https://twitter.com/DeanPlbn

    • 1 hr 2 min
    🤖 GPTs & Large Language Models in production with Hamel Husain

    🤖 GPTs & Large Language Models in production with Hamel Husain

    In this episode, I had the pleasure of speaking with Hamel Husain. Hamel is a machine learning and MLOps extraordinaire, he was one of the core maintainers of Fast.ai and has worked on ML and MLOps in places like Data Robot, Airbnb, and GitHub. We talk about Large Language Models, the future role of data scientists in the world of LLMs, and Hamel's approach to solving MLOps problems.

    Watch the video: https://www.youtube.com/watch?v=3oElMXPkaVs

    Relevant Links:
    🐦 Hamel's Twitter – https://twitter.com/HamelHusain
    🟦 Hamel's Linkedin – https://www.linkedin.com/in/hamelhusain/
    ✍️ Hamel's amazing blog: https://hamel.dev/blog/posts/nbdev/

    🌐 Check Out Our Website! https://dagshub.com

    Social Links:
    ➡️ LinkedIn: https://www.linkedin.com/company/dagshub
    ➡️ Twitter: https://twitter.com/TheRealDAGsHub
    ➡️ Dean Pleban: https://twitter.com/DeanPlbn

    • 1 hr 5 min

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