An Era of Relevance What is the nature of this tech revolution? Business & Data Understanding in AI/ML Part 1. Part of a larger series on Full-Stack AI/ML in Production. Intro What is the nature of this tech revolution? How can businesses leverage AI/ML for impact? Hotly debated questions. Lots of
Engineering Design Process for AI/ML Projects Intro How can you deploy AI/ML systems while reducing cost, time, and risk as much as possible? Applying the Engineering Design Process to new AI/ML projects is an efficient roadmap to deploying the three core systems we covered in the last post on Full-Stack AI/ML in Production.
Featured Full-Stack AI/ML in Production Intro What does it really take to deploy and maintain machine learning systems in production? You know how it is. There are nearly infinite tutorials on training machine learning models that start with a jupyter notebook then end with a trained model. Then it's... draw the rest of
computer vision Featured Most Popular CV Model Types What if a baby monitor video stream could alert you if your baby is in a dangerous position at night? What if you could use sign language to control your tv and speakers? What if cars drove themselves? These are some of the interesting tasks that computer vision makes possible.
image annotations Featured Intro to Image Annotations What is image annotation? Image annotation, in the context of machine learning, is when you take any image you want to train and label it in a way you can train a model. So annotation is synonymous with label or class. Here is a simple example: Taco or Cowboy Hat?
TDD Part 1 First lets define TDD. After a quick google around I found a pretty good summary of the methodology here:
Some D3 Tips and Tricks I’m currently working on a deep learning journal called ReadMe (…get it). For this project I have been working on displaying the…
