Home » Implement a data science and machine learning solution for AI with Microsoft Fabric (DP-604)

Implement a data science and machine learning solution for AI with Microsoft Fabric (DP-604)

Leer data te ontdekken en voorbewerken, vervolgens modellen te trainen, volgen en in te zetten.
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Cursusbeschrijving

Verken het data science proces en leer hoe je machine learning-modellen traint om kunstmatige intelligentie (AI) te bereiken in Microsoft Fabric.

Onderwerpen

  • Get started with data science in Microsoft Fabric
  • Understand the data science process
  • Train models with notebooks in Microsoft Fabric
  • Track model training metrics with MLflow and experiments
  • ### Explore data for data science with notebooks in Microsoft Fabric
  • Load data and perform initial data exploration.
  • Gain knowledge about different types of data distributions.
  • Understand the concept of missing data, and strategies to handle missing data effectively.
  • Visualize data using various data visualization techniques and libraries.
  • ### Preprocess data with Data Wrangler in Microsoft Fabric
  • Learn Data Wrangler features, and its role in the data science workflow.
  • Perform different types of preprocessing operations in data science.
  • Learn how to handle missing values, and imputation strategies.
  • Use one-hot encoding and other techniques to convert categorical data into a format suitable for machine learning algorithms.
  • ### Train and track machine learning models with MLflow in Microsoft Fabric
  • Train machine learning models with open-source frameworks
  • Train models with notebooks in Microsoft Fabric
  • Track model training metrics with MLflow and experiments in Microsoft Fabric
  • ### Generate batch predictions using a deployed model in Microsoft Fabric
  • Save a model in the Microsoft Fabric workspace
  • Prepare a dataset for batch predictions
  • Apply the model to dataset to generate new predictions
  • Save the predictions to a Delta table

    • Materiaal

    Digitaal Microsoft cursusmateriaal

    Voorkennis

    Bekend met basisconcepten en terminologie rond data.