MLA 021 Databricks
Machine Learning Guide
Discussing Databricks with Ming Chang from (part of )
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MLA 020 Kubeflow
Machine Learning Guide
Conversation with Dirk-Jan Kubeflow (vs cloud native solutions like SageMaker) - Data Scientist at Dept Agency . (From the website:) The Machine Learning Toolkit for Kubernetes. The Kubeflow project is dedicated to making deployments of machine learning (ML) workflows on Kubernetes simple, portable and scalable. Our goal is not to recreate other services, but to provide a straightforward way to deploy best-of-breed open-source systems for ML to diverse infrastructures. Anywhere you are running Kubernetes, you should be able to run Kubeflow. . If using TensorFlow with Kubeflow, combine...
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MLA 019 DevOps
Machine Learning Guide
Chatting with co-workers about the role of DevOps in a machine learning engineer's life Expert coworkers at Dept - Principal Software Developer - DevOps Lead (where Matt features often) Devops tools Pictures (funny and serious)
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MLA 018 Descript
Machine Learning Guide
(Optional episode) just showcasing a cool application using machine learning Dept uses Descript for some of their podcasting. I'm using it like a maniac, I think they're surprised at how into it I am. Check out the transcript & see how it performed. How to ship software, from the front lines. We talk with software developers about their craft, developer tools, developer productivity and what makes software development awesome. Hosted by your friends at Rocket Insights. AKA shipit.io An agency podcast with views on design, technology, art, and culture. Explore the new...
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MLA 017 AWS Local Development
Machine Learning Guide
Show notes: Developing on AWS first (SageMaker or other) Consider developing against AWS as your local development environment, rather than only your cloud deployment environment. Solutions: Stick to AWS Cloud IDEs (, , Connect to deployed infrastructure via Infrastructure as Code
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MLA 016 SageMaker 2
Machine Learning Guide
Part 2 of deploying your ML models to the cloud with SageMaker (MLOps) MLOps is deploying your ML models to the cloud. See for an overview of tooling (also generally a great ML educational run-down.)
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MLA 015 SageMaker 1
Machine Learning Guide
Part 1 of deploying your ML models to the cloud with SageMaker (MLOps) MLOps is deploying your ML models to the cloud. See for an overview of tooling (also generally a great ML educational run-down.) And I forgot to mention , I'll mention next time.
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MLA 014 Machine Learning Server
Machine Learning Guide
Server-side ML. Training & hosting for inference, with a goal towards serverless. AWS SageMaker, Batch, Lambda, EFS, Cortex.dev
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MLA 013 Customer Facing Tech Stack
Machine Learning Guide
Client, server, database, etc.
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MLA 012 Docker
Machine Learning Guide
Use Docker for env setup on localhost & cloud deployment, instead of pyenv / Anaconda. I recommend Windows for your desktop.
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