Description for MLOps in R: Deploying machine learning models using vetiver
Developing a Stacked Ensemble Model: Comprehend the process of preparing and constructing a layered ensemble model for deployment.
Versioning and Deployment with Vetiver: Acquire the knowledge necessary to version and deploy machine learning models using Vetiver, thereby guaranteeing seamless updates and management.
Monitoring and Predictive Analytics: Utilize methodologies to anticipate and supervise model functionality, guaranteeing consistent precision over time.
Pipeline for Automated Deployment: Utilize realistic scenarios, such as the deployment of a hospital readmission model, to establish and effectively manage a fully automated deployment pipeline.
Level: Intermediate
Certification Degree: Yes
Languages the Course is Available: 1
Offered by: On Coursera provided by Coursera Project Network
Duration: 2 hours at your own pace
Schedule: Hands-on learning
Pricing for MLOps in R: Deploying machine learning models using vetiver
Use Cases for MLOps in R: Deploying machine learning models using vetiver
FAQs for MLOps in R: Deploying machine learning models using vetiver
Reviews for MLOps in R: Deploying machine learning models using vetiver
0 / 5
from 0 reviews
Ease of Use
Ease of Customization
Intuitive Interface
Value for Money
Support Team Responsiveness
Alternative Tools for MLOps in R: Deploying machine learning models using vetiver
Accelerate your career in data analytics. In this certificate program, you will acquire skills that are in high demand at your own tempo, regardless of your degree or experience.
Prepare for a vocation as a data scientist. Acquire hands-on experience and in-demand skills to become job-ready in as little as five months. No prior experience is necessary.
This AI course delineates the Data Scientist's toolkit, instructs students in Python, R, and SQL, investigates RStudio and Jupyter notebooks, and discusses Git and GitHub for source code administration.
Potential for data-driven decision-making has been realized. Students will acquire the skills to access, manage, analyze, and visualize data to secure a competitive edge in strategic business decision-making.
Develop a machine learning pipeline that utilizes Tidymodels to forecast hospital readmissions, with potential applications in healthcare analytics.
Featured Tools
The course's main objectives are to deploy solutions using Vertex AI and integrate machine learning into Google Cloud data pipelines, such as AutoML and BigQuery ML.
Acquire the skills necessary to program powerful systems in Rust. Through projects in data engineering, Linux tools, DevOps, LLMs, Cloud Computing, and machine learning operations, acquire the skills necessary to develop software that is both efficient and robust, utilizing Rust's distinctive safety and speed.
Begin Your Professional Journey in Self-Driving Vehicles. Be at the vanguard of the autonomous driving industry.
Acquire knowledge of machine learning by examining actual applications. Develop the necessary skills for a vocation in one of the most pertinent areas of contemporary AI by participating in hands-on projects and completing coursework from IBM's experts.
Learn how to apply prompt engineering methods in generative AI to create input-output pairs, address real-world problems, and implement suitable techniques for everyday applications.