Monday, August 30, 2021

TensorFlow.js Setup for React JS App (Manning liveProject)

I explain the structure of my liveProject. It is a series of five projects, I use the first one as an example (it is free). React is highly prized by developers for its ease of building simple and intuitive frontends. liveProject teaches how to use Machine Learning directly within React code and run it in the browser. After working on this liveProject, you will learn how to run PoseNet model, use data collected by PoseNet to train your own custom ML model with TensorFlow.js. React application will help to track physical workout movements, classify them and count statistics.

 

Monday, August 23, 2021

Routing Traffic Between FastAPI Pods in Kubernetes

This is a quick tutorial to show how to route traffic between Kubernetes Pods. Both Pods are running FastAPI endpoints. I show how to create Deployment and Service elements for Kubernetes Pod, and how to refer to that service from another Pod to execute HTTP call.

 

Thursday, August 19, 2021

Human Pose Estimation with TensorFlow.js and React

Want to learn #MachineLearning and #React by doing? My @ManningBooks liveProject 'Human Pose Estimation with TensorFlow.js and React' is published. Free access to Manning books is included. Try it here.

Monday, August 9, 2021

FastAPI Running on Kubernetes Pod

Step-by-step tutorial where I explain and show how to run FastAPI app on Kubernetes Pod. I keep it simple. I explain when it makes sense to use multiple containers in a single Pod and when you should put containers into different Pods.

 

Monday, August 2, 2021

Dockerfile and Docker Compose Tutorial for MLOps

This is the tutorial, where I talk about MLOps, explain the difference between Dockerfile and Docker Compose YML definition file. I briefly explain what you should be aware of if planning to move your solution to Kubernetes in the future. I explain in simple words, what is Dockerfile and when Docker Compose is useful. The sample service is based on TensorFlow functionality, where we call model predict function to process serving request.