Deploy a predictive machine learning model using IBM Cloud

ofrecido por
Coursera Project Network
En este proyecto guiado, tú:

Create, evaluate and deploy a machine learning model using Watson Studio (without writing a single line of code).

Deploy the model and try out as a web service frontend to make predictions.

Clock2 hours
IntermediateIntermedio
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

In this 1-hour long project-based course, you will be able to create, evaluate and save a machine learning model (without writing a single line of code) using Watson Studio on IBM Cloud Platform, and you will make deployment of the model and try out as a web service frontend to make predictions. This guided project is for Data Scientists, Machine Learning Engineers, and Developers who want a way to deliver their machine learning code available to be integrated into an application and using it as a web service. We will do everything in a development mode without any costs using a free IBM Cloud account. To be successful in this project, you should be familiar with machine learning methodologies, like training, prediction, evaluation, and basic knowledge in some machine learning algorithms is appreciated too, so that way you will understand the results before making a deployment. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Habilidades que desarrollarás

  • Data Science
  • deployment
  • Machine Learning
  • Classification Algorithms
  • Machine Learning (ML) Algorithms

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  1. Introduction to the IBM Cloud and Watson Studio.

  2. Create a Project and Import our Data.

  3. Explore the Data Refinery and create a Machine Learning Service.

  4. Train, evaluate and save the Machine Learning model.

  5. Deploy and test the ML model as a Web Service.

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

Preguntas Frecuentes

Preguntas Frecuentes

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