Previzionați, gestionați și monitorizați picăturile de apel ale turnurilor de celule folosind IBM Cloud Pak pentru date

Marca temporală: 18 august 2020 12:00
Nodul sursă: 748601

Rezumat

This code pattern is part of a series that explores telecom call-drop predictions using IBM Cloud Pak® for Data, data virtualization, IBM Watson® OpenScale™, and Cognos® Analytics.

Descriere

This code pattern will show you how to create a model to predict call drops. With the help of an interactive dashboard, we’ll use a time series model to better understand call drops.

In this code pattern, you’ll learn how to:

  • Use data virtualization
  • Create connections from databases hosted on multiple cloud (AWS, Azure, or IBM Cloud) or on-premises environments
  • Create views from joins and publish data to your current project
  • Stocați modele personalizate folosind tehnologia open source pe Watson Machine Learning
  • Implementați un model și conectați implementarea modelului la Watson OpenScale pe IBM Cloud Pak for Data și IBM Cloud
  • Set up model fairness and model quality monitors in Watson OpenScale on IBM Cloud Pak for Data and on IBM Cloud using a Python notebook
  • Create a project and set up a Python notebook on IBM Cloud Pak for Data

Debit

Predict and manage calls flow diagram

  1. AI models virtualize and join data stored across various sources, like AWS Cloud and IBM Cloud, as needed.
  2. Joined data is stored in the internal database of IBM Cloud Pak for Data and assigned to the current working project.
  3. Create machine learning models using Jupyter Notebooks to predict call drops per tower and a time-series model that projects a call-drop percentage based on real-time conditions.
  4. Model trained and stored in Watson Machine Learning, which is also connected to Watson OpenScale.
  5. Visualize and analyze insights from the trained models and the data using Cognos Analytics dashboards.
  6. Configure fairness, quality, and explainability monitors for each tower’s model.

Instrucțiuni

Găsiți pașii detaliate pentru acest model în README. Pașii vă arată cum să:

  1. Clonați depozitul.
  2. Obtain your data from data virtualization.
  3. Creați un nou proiect în IBM Cloud Pak for Data.
  4. Upload the data set to IBM Cloud Pak for Data.
  5. Import the notebook to IBM Cloud Pak for Data.
  6. Urmați pașii din caiet.
  7. Set up your notebook for call drop monitoring.
  8. Set up the Cognos Analytics Dashboard on your IBM Cloud Pak for Data instance for visualizations.

Sursa: https://developer.ibm.com/patterns/predict-manage-and-monitor-the-call-drops-of-cell-tower-using-cloud-pack-for-data/

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