Recommender Systems from A to Z – Real-Time Deployment


Details
In the last year, there have been a lot of improvements done in the field of Machine Learning and the tools that support the community of developers. Still, implementing a recommender system is very hard.
That is why at Crossing Minds, we have decided to create a series of four meetups to discuss how to implement a recommender system end-to-end:
Part 1 – The Right Dataset
Part 2 – Model Training
Part 3 – Model Evaluation
Part 4 – Real-Time Deployment
This fourth meetup will present good practices and tips about deploying a recommender system in production. We will cover a wide range of the day-to-day of machine learning engineers and devops: from test-driven development to continuous integration and cloud architecture design. We will see how machine learning and recommender system in particular differ from traditional software development, and how this impacts deployment pipelines, and what tools you can use to solve this problem.
Speaker
CTO at Crossing Minds, Emile Contal
Agenda
6:30pm - 6:45pm Meet and Greet
6:45pm - 7:30pm Speakers
7:30pm - 8:00pm Q&A
Additional Notes
Previous Meetup Slides:
Recommender Systems from A to Z - The Right Dataset: https://www.slideshare.net/CrossingMinds/recommender-systems-from-a-to-z-the-right-dataset
Recommender Systems from A to Z – Model Training: https://www.slideshare.net/CrossingMinds/recommender-systems-from-a-to-z-model-training
Recommender Systems from A to Z – Model Evaluation: https://www.slideshare.net/CrossingMinds/recommender-systems-from-a-to-z-model-evaluation
We'll have food. Lot of food!

Recommender Systems from A to Z – Real-Time Deployment