
Sign up to save your podcasts
Or


Today we’re joined by Emmanuel Ameisen, machine learning engineer at Stripe, and author of the recently published book “Building Machine Learning Powered Applications; Going from Idea to Product.” In our conversation, we discuss structuring end-to-end machine learning projects, debugging and explainability in the context of models, the various types of models covered in the book, and the importance of post-deployment monitoring.
By Sam Charrington4.7
422422 ratings
Today we’re joined by Emmanuel Ameisen, machine learning engineer at Stripe, and author of the recently published book “Building Machine Learning Powered Applications; Going from Idea to Product.” In our conversation, we discuss structuring end-to-end machine learning projects, debugging and explainability in the context of models, the various types of models covered in the book, and the importance of post-deployment monitoring.

1,105 Listeners

168 Listeners

305 Listeners

343 Listeners

233 Listeners

209 Listeners

205 Listeners

314 Listeners

100 Listeners

551 Listeners

146 Listeners

102 Listeners

228 Listeners

685 Listeners

34 Listeners