Meetup #47

ProductizeML: Assisting Your Team to Better Build ML Products

In this talk we will talk about: - Motivations and mission behind ProductizeML. - Common friction points and miscommunication between technical and management/product teams, and how to bridge these gaps. - How to define ML product roadmaps, (and more importantly, how to get it signed off by all your team). - Best practices when managing the end-to-end ML lifecycle.

In this episode

Adria Romero

Adria Romero

Founder and Instructor, ProductizeML

Adria is an AI, ML, and product enthusiast with more than 4 years of professional experience on his mission to empower society with data and AI-driven solutions. Born and raised in the beautiful and sunny Barcelona, he began his journey in the AI field as an applied researcher at the Florida Atlantic University, where he published some of the first deep learning works in the healthcare sector. Attracted by the idea of deploying these ideas to the real world, he then joined Triage, a healthcare startup building healthcare solutions powered by AI, such a smartphone app able to detect over 500 skin diseases from a picture. During this time, he has given multiple talks at conferences, hospitals, and institutions such as Novartis and Google. Previously, he interned at Huawei, Schneider Electric, and Insight Center for Data Analytics. Early this year, he started crafting ProductizeML, an instruction and interactive guide for teams building Machine Learning products where he and a team of AI & product specialists carefully prepare content to assist on the end-to-end ML lifecycle.

@adriaromero

LinkedIn

Demetrios Brinkmann

Demetrios Brinkmann

Host

Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.