New Year, New Starts: Two Tutorials to kick of 2023 with new skills
Excited to announce we have two speakers for January! It is jam backed to kick off 2023 strong.
We are going to explore:
- how to use AI to learn a new coding language and
- how to build a modern MLOps application.
NOTE: The MLOps Tutorial will span both January and February meetups. To get the most out of this meet up please bring a computer with Python and docker installed.
ML & AI Software Development 101: An Interactive Workshop
Join us for a live, interactive workshop on how to set up your machine learning engineering software development environment to build and deploy production ML models like a professional.
Greg Loughnane, Ph.D., Head of Product & Curriculum at FourthBrain, will walk through how to set up your computer to do industry-standard machine learning software development, including all essential tools and libraries, and will demonstrate how to build and deploy a simple ML web application using the development environment. Attendees will learn how to set up their own dev environment and replicate an end-to-end ML production application, including all necessary setup and deployment code.
This workshop is perfect for anyone looking to get started with machine learning software development or anyone interested in becoming a machine learning engineer. This session is also ideal for anyone just looking to learn more about end-to-end MLOps deployments.
Who should attend the event?
- Learners interested in getting started with ML software development, and who already have some understanding of Python and Data Science.
- Learners interested in deploying end-to-end production ML applications using industry-standard tools.
- Learners interested in the industry-standard tool stack for machine learning engineers and other ML practitioners in 2023.
Why should you attend the event?
- To learn how to set up your own ML software dev environment.
- To understand the software development stack you need to succeed in industry.
- To learn how to replicate an end-to-end production deployment using standard tools.
Part I (January): Interactive Development Environment Setup and Configuration
- (10 min) Overview and demonstration of key tools for MLOps Development Workflows; VSCode (IDE), Git (version control), Unix Command Line Interface (terminal/interact with OS), Conda (data science package and environment manager)
- (20 min) Working session ~ install VSCode, Git, CLI, and Conda!
Part II (February): First ML App Deployment!
10 min ~ Overview and demonstration of key tools for MLOps Deployments; FastAPI (Python web application framework), Docker (containerization)
20 min working session ~ install FastAPI and Docker!
**All Users Note: The easiest method for using Docker is to leverage Docker Desktop, and we recommend installing prior to the session!
Windows, Mac, and Linux OS are all welcome!
- Windows Users Note: please install Windows Subsystem for Linux (WSL 2) prior to the session!