Monday, July 19, 2021

Serving ML Model with Docker, RabbitMQ, FastAPI and Nginx

In this tutorial I explain how to serve ML model using such tools as Docker, RabbitMQ, FastAPI and Nginx. The solution is based on our open-source product Katana ML Skipper (or just Skipper). It allows running ML workflow using a group of microservices. It is not limited to ML, you can run any workload using Skipper and plugin your own services. You can reach out to me if you got any questions.

 

Wednesday, July 14, 2021

TensorFlow Decision Forests Example

With TensorFlow Decision Forests we can handle structured data without much preprocessing. There is no need to normalize numeric values, one-hot encode categorical values, or set magic values to replace missing data. I give it a try and run this new feature of TensorFlow in this video. The demo is based on the Titanic dataset taken from Kaggle.

 

Monday, June 28, 2021

FastAPI Background Tasks for Non-Blocking Endpoints

With FastAPI it is super easy to implement a non-blocking endpoint. This is useful when the endpoint calls logic, which should be executed asynchronously and you don't need to wait for the result, but want to return a response immediately. For example - a service that does logging. We don't want to wait until the log will be written but return the response instantly.

 

Monday, June 21, 2021

Publishing Your Python Library on PyPI

I explain how to publish Python library on PyPI with Poetry. I believe this video will be useful to all Python developers, who are looking at how to create Python library and publish it. I share my experience and explain why I spent the entire day debugging the issue with library dependencies.

 

Monday, June 7, 2021

ML Pipeline End-to-End Solution

Are you interested to learn how to build and run a complete ML pipeline - Web API, data processing, model training, and prediction services? In this video, I explain how the end-to-end solution works using our open-source product Skipper.

 

Monday, May 31, 2021

FastAPI Endpoint Type with Pydantic

Pydantic library helps to define structured and clear types for FastAPI endpoints. In this video I explain how to define Pydantic type with nested list structure, I show how it works with a live demo. You will get to know how to convert input data into JSON structure. Enjoy!

 

Monday, May 24, 2021

Event-Driven Microservice with RabbitMQ and FastAPI

Event-driven microservices architecture brings scalability and better application structure. In this video, I show a demo based on Web API implementation with FastAPI, Celery. The event is sent to a group of microservices through RabbitMQ broker. Services communicate with each other through RabbitMQ. Model training service calls data service to fetch and prepare data for training.