- Serving ML Models in Production: Common Patterns - Oct 18, 2021.
Over the past couple years, we've seen 4 common patterns of machine learning in production: pipeline, ensemble, business logic, and online learning. In the ML serving space, implementing these patterns typically involves a tradeoff between ease of development and production readiness. Ray Serve was built to support these patterns by being both easy to develop and production ready.
FastAPI, Machine Learning, Production, Python, Ray
Deploying Your First Machine Learning API - Oct 14, 2021.
Effortless way to develop and deploy your machine learning API using FastAPI and Deta.
API, Deployment, FastAPI, Machine Learning, Python, spaCy
- ColabCode: Deploying Machine Learning Models From Google Colab - Jul 22, 2021.
New to ColabCode? Learn how to use it to start a VS Code Server, Jupyter Lab, or FastAPI.
Deployment, FastAPI, Google Colab, Machine Learning, Python
- How to Create and Deploy a Simple Sentiment Analysis App via API - Jun 1, 2021.
In this article we will create a simple sentiment analysis app using the HuggingFace Transformers library, and deploy it using FastAPI.
FastAPI, Hugging Face, NLP, Python, Sentiment Analysis, Transformer
- Deploy a Dockerized FastAPI App to Google Cloud Platform - May 4, 2021.
A short guide to deploying a Dockerized Python app to Google Cloud Platform using Cloud Run and a SQL instance.
API, Deployment, Docker, FastAPI, Google Cloud
- Production-Ready Machine Learning NLP API with FastAPI and spaCy - Apr 21, 2021.
Learn how to implement an API based on FastAPI and spaCy for Named Entity Recognition (NER), and see why the author used FastAPI to quickly build a fast and robust machine learning API.
API, FastAPI, NLP, Production, Python, spaCy
