MLOps1 (GCP): Deploying AI & ML Models in Production using Google Cloud Platform
Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how data engineers can effectively work with data scientists to monitor and iterate on model performance, which is why we developed this course: MLOps1 (GCP) - Deploying AI & ML Models in Production using Google Cloud Platform

There is one session available:
MLOps1 (GCP): Deploying AI & ML Models in Production using Google Cloud Platform
Most data science projects fail. There are various reasons why, but one of the primary reasons is the challenge of deployment. One piece to the deployment puzzle is understanding how data engineers can effectively work with data scientists to monitor and iterate on model performance, which is why we developed this course: MLOps1 (GCP) - Deploying AI & ML Models in Production using Google Cloud Platform

There is one session available:
MLOps1 (GCP): Deploying AI & ML Models in Production using Google Cloud Platform
At a glance
- Institution: Statistics.comX
- Subject: Computer Science
- Level: Intermediate
- Prerequisites:
- Predictive Analytics: Basic Modeling Techniques
- Participants should be comfortable working with Python in a cloud-based environment, and will gain maximum benefit if they have some familiarity with software development, including git, logging, testing, debugging, code optimization and security.
- Language: English
- Video Transcript: English
- Associated programs:
- Professional Certificate in Machine Learning Operations with Google Cloud Platform (MLOps with GCP)