Enterprise MLOps Interviews

Enterprise MLOps Interviews

by Alfredo Deza, Noah Gift
Released January 2024
Publisher(s): Pragmatic AI Labs
ISBN: 08012022VIDEOPAIML

Watch it now on the O’Reilly learning platform with a 10-day free trial.

O’Reilly members get unlimited access to books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.

Start your free trial

Video description

Enterprise MLOps Interviews

Learn Enterprise MLOps from the experts

This video series interviews the experts at MLOps to learn how to use MLOps to build and deploy ML models.

Interviews Include:

  • 1.0: Introduction
  • 2.0: GPT-3: O'Reilly authors Shubham Saboo and Sandra Kublik:
    • I talk with the authors of the new O'Reilly book GPT-3 about a range of topics, including why they wrote the book.
  • 3.0: Conversation with Piero Molino and Ludwig/Predibase:
    • Detailed conversation about Declarative AutoML with Piero Molino, author of Ludwig and co-founder Predibase.
  • 4.0: Asaf Somekh, CEO Iguazio:
    • Talk at Duke MIDS MLOps Course: Life of a Model (or the brutal reality of applying ML in enterprises and how to deal with it).
  • 5.0: Javier Luraschi and Pedro Luraschi, Co-Founders of Hal9.ai:
    • Discuss MLOps with Javascript, including no-code and low-code approaches and Tensorflow.js.
  • 6.0: Malcolm Smith Fraser, ML Engineer at DoorDash and graduate student at Duke University MIDS
    • Discuss building an MLOps pipeline with AWS components including SQS, Lambda and Batch.
  • 7.0: Jon Reifschneider, Head of Artificial Intelligence Product Innovation at Duke University
    • Discuss the role of MLOps in the AI industry as well as demonstrate how MLOps can be used to build career mapping tools.
  • 8.0: Julien Simon, Hugging Face
    • Discuss the use of MLOps via pre-trained models and how to use MLOps to build and deploy models as well as create a career.
  • 9.0: Shubham Saboo and Noah Gift on MLOps and GPT-3 do live coding and cover both AWS and OpenAI in codespaces.
  • 10.0: Discuss MLOps with long-time Python guru Brian Ray, managing director of Maven Wave, and Atos Company.
  • 11.0: Simon Stebelena is the lead MLOps engineer at Transaction Monitoring Netherlands.
  • 12.0: Bindu Reddy the CEO of Abacus AI talks about the role of MLOps in the AI industry and how to use MLOps to build and deploy models as well as opportunities in the space.
  • 13.0: Dhanasekar Sundararaman Duke Phd in Computer Engineering and Microsoft Researcher discusses how to process numbers in NLP models and discusses Hugging Face.
  • 14.0: Ville Tuulos the CEO of Outerbounds and the Open Source Framework Metaflow has a conversation about MLOPs including his time building systems for Netflix.
  • 15.0: Lewis Tunstall and Leandro von Werra of Hugging Face discuss MLOps with Hugging Face and how to use MLOps to build and deploy models as well as create a career.
  • 16.0: Arvs Lat Author of Machine Learning Engineering on AWS
  • 17.0: Julien Simon Yaron Haviv Noah Gift MLRun Hugging Face MLOps Seminar
  • 18.0: Nic Stone CTO of Crul - discusses building automated data pipelines
  • 19.0: Enterprise MLOps Interviews Doris Xin Founder of Linea AI
  • 20.0: Chat with Maxime David. We discuss Rust and how it makes for an ideal language for AWS Lambda. Checkout his Rust YouTube Channel here: @maxday_coding and his lambda-perf repo here: https://github.com/maxday/lambda-perf
  • 21.0: Chat with Jason McCampbell about the use of Rust @Wallaroo.AI
  • 22.0: O'Reilly Author-Adi Polak-Interview about Scaling Machine Learning with Spark
  • 23.0: O'Reilly Author-Ole Olesen-Bagneux-The Enterprise Data Catalog
  • 24.0: A Conversation on ethical AI with creator and thought leader Johan Cedmar-Brandstedt.
rust #switchtorust #python #mlops Topics Covered Include:

Enterprise MLOps

  • MLOps
  • MLOps on AWS
  • MLOps on GCP
  • MLOps on Azure
  • MLOps and DevOps
  • MLOps with Ludwig
  • Feature Engineering
  • MLOps with Tensorflow.js
  • MLOps with Pytorch
  • Building career paths with MLOps
  • Duke and Coursera
  • 10 step to MLOps in the Enterprise
Learning Objectives
  • Create a Github Repo and launch it in a Codespaces instance
  • Create a Jupyter Notebook and save it to a Colab instance
  • Ingest Data from a CSV file into a Jupyter Notebook
  • Do EDA
  • Build and test your data science project with Github Actions and nbval
Additional Popular Resources

Product information

  • Title: Enterprise MLOps Interviews
  • Author(s): Alfredo Deza, Noah Gift
  • Release date: January 2024
  • Publisher(s): Pragmatic AI Labs
  • ISBN: 08012022VIDEOPAIML