Most software development teams have adopted continuous integration and delivery (CI/CD) to iterate faster. However, a machine learning model depends not only on the code but also the data and hyperparameters. Releasing a new machine learning model in production is more complex than traditional software development.

Finding the right subreddit to submit your post can be tricky, especially for people new to Reddit. There are thousands of active subreddits with overlapping content. If it is no easy task for a human, I didn’t expect it to be easier for a machine. Currently, redditors can ask for suitable subreddits in a special subreddit: r/findareddit.

When doing machine learning in production, the choice of the model is just one of the many important criteria. Equally important are the definition of the problem, gathering high-quality data and the architecture of the machine learning pipeline.

Apache Airflow is a popular platform to create, schedule and monitor workflows in Python. It has more than 15k stars on Github and it’s used by data engineers at companies like Twitter, Airbnb and Spotify.