Full working example to serve your model using asynchronous Celery tasks and FastAPI.
Overview
There is an abundance of material online related to building and training all kinds of machine learning models. However once a high performance model has been trained there is significantly less material for how to put it into production.
This post walks through a working example for serving a ML model using Celery and FastAPI. All code can be found in the repository here.
We won’t specifically discuss the ML model used for this example however it was trained using example Bank customer churn data (https://www.kaggle.com/sakshigoyal7/credit-card-customers). …
Keep up-to-date with public sentiment using live tweets and an easy-to-build Streamlit web app.
Twitter can be used as a data source for various data science projects, including Geo-spatial analysis (where are users tweeting about certain subjects?) and sentiment analysis (how do users feel about certain subjects?).
I decided to build a dashboard that combines the two questions using the example of UK political leaders; Boris Johnson and Keir Starmer. However it’s possible to use any combination of keywords to analyse political figures, companies etc.
We can break down what needs to be done into three distinct areas:
- Database set-up: This can be done directly in the RDBMS of your choice, however we choose…
Jonathan Readshaw
Engineering graduate with a passion for Data Science and ML. https://www.linkedin.com/in/jonathan-readshaw-4884b2147/
