Machine Learning Operations (MLOps): Getting Started
|
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud.
This course introduces participants to MLOps tools and best practices for deploying, evaluating, monitoring and operating production ML systems on Google Cloud. MLOps is a discipline focused on the deployment, testing, monitoring, and automation of ML systems in production. Machine Learning Engineering professionals use tools for continuous improvement and evaluation of deployed models. They work with (or can be) Data Scientists, who develop models, to enable velocity and rigor in deploying the best performing models.
Author Name: Google Cloud
Author Description:
Google Cloud can help solve your toughest problems and grow your business. With Google Cloud, their infrastructure is your infrastructure. Their tools are your tools. And their innovations are your innovations.
Table of Contents
- Welcome to the Machine Learning Operations (MLOps): Getting Started
4mins - Employing Machine Learning Operations
24mins - Vertex AI and MLOps on Vertex AI
31mins - Summary
2mins
User Reviews
Be the first to review “Machine Learning Operations (MLOps): Getting Started”
Related Products
Intro to Deep Learning with TensorFlow
Build basic deep learning models in TensorFlow.
Build Chatbots with Python
Build rules-based and generative AI chatbots with Python
Intro to Cloud Computing
Learn the foundations of cloud computing across platforms like AWS, Cloud, Azure, and GCP.
Data and Programming Foundations for AI
Learn the coding, data science, and math you need to get started as a Machine Learning or AI engineer.
Machine Learning/AI Engineer
Machine Learning/AI Engineers build end-to-end ML applications and power many of the apps we use every day. They work in Python, Git, & ML.
Machine Learning: Logistic Regression
Predict the probability that a datapoint belongs to a given class with Logistic Regression.
There are no reviews yet.