Series Path · 5 parts
MLOps & Model Serving
Orchestrating and serving ML models in production — Kubeflow pipelines on Kubernetes and LitServe deployment with Docker.
Curriculum — 5 parts
- 01
Kubeflow: A Comprehensive Guide to Machine Learning on Kubernetes
Kubeflow is an open-source machine learning platform designed to make deployments of machine learning workflows on Kubernetes simple, portable, and scalable.…
12 min read - 02
Kubeflow Deep Learning Guide with PyTorch
Kubeflow is a machine learning toolkit for Kubernetes that makes deployments of ML workflows on Kubernetes simple, portable, and scalable. This guide focuses…
9 min read - 03
LitServe Code Guide
LitServe is a high-performance, flexible AI model serving framework designed to deploy machine learning models with minimal code. It provides automatic…
8 min read - 04
LitServe with MobileNetV2 - Complete Code Guide
This guide demonstrates how to deploy a MobileNetV2 image classification model using LitServe for efficient, scalable inference.
9 min read - 05
MobileNetV2 PyTorch Docker Deployment Guide
This guide walks you through deploying a pre-trained MobileNetV2 model using PyTorch and Docker, creating a REST API for image classification.
11 min read