with Mia Chang
Date: 27 April 2020
Time: 19:00 - 20:00 GMT
About the episode
About the talk
What was your last AI project? Was it another Kaggle dataset running on Jupyter notebook, hard to reproduce and don't know how to deploy as an AI service? How to do auto-scaling for the model serving?
How far is the distance from playing with the sample dataset to AI production?
Let's go through 7 steps in the AI application development lifecycle. From data wrangling, reproduce your training, model acceptance to model deployment and management.
Target audience: Data scientist who doesn't know the model serving and Azure DevOps. Backend/DevOps who doesn't know how to help your data team go production.
Mia comes with a mathematics and computer science background. She works as a data scientist in Berlin. In her career path, from backend engineer, data consultant to a data scientist, from traditional AI theory to practical industry experience. She is also be recognized as Microsoft AI MVP, focus on computer vision and deep learning applications. You may find her speaking in different tech events, delivering workshops, having podcasts on channel 9 or see her dedicating her passion for hackathons. She also published her first co-author book, Microsoft AI MVP Book on Amazon Kindle in 2019. Feel free to reach out to her about data science project/architect or MLOPs topics.
- 7PM (GMT+1, Brussels)
People in this episode
Host of the AI Talks
Data Scientist, Microsoft AI MVP