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DP-3014 Implementing a Machine Learning solution with Azure Databricks

$295 - $695

Upgrade your tech skills with this , training course. Launch your career to the stars with AstraTech IT Certification Training!

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    • Microsoft Azure
    • Microsoft Technical

    Course Highlights
    ILT DURATION: 1 Day(s)
    SKILL LEVEL: 
    • Intermediate
    BRAND/TECHNOLOGY: 
    TOPICS: 

    DP-3014 Implementing a Machine Learning solution with Azure Databricks Course Outline

    Azure Databricks is a cloud-scale platform for data analytics and machine learning. Data scientists and machine learning engineers can use Azure Databricks to implement machine learning solutions at scale.

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    This learning path assumes that you have experience of using Python to explore data and train machine learning models with common open source frameworks, like Scikit-Learn, PyTorch, and TensorFlow.

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    1 – Explore Azure Databricks

    • Get started with Azure Databricks
    • Identify Azure Databricks workloads
    • Understand key concepts

    2 – Use Apache Spark in Azure Databricks

    • Get to know Spark
    • Create a Spark cluster
    • Use Spark in notebooks
    • Use Spark to work with data files
    • Visualize data

    3 – Train a machine learning model in Azure Databricks

    • Understand principles of machine learning
    • Machine learning in Azure Databricks
    • Prepare data for machine learning
    • Train a machine learning model
    • Evaluate a machine learning model

    4 – Use MLflow in Azure Databricks

    • Capabilities of MLflow
    • Run experiments with MLflow
    • Register and serve models with MLflow

    5 – Tune hyperparameters in Azure Databricks

    • Optimize hyperparameters with Hyperopt
    • Review Hyperopt trials
    • Scale Hyperopt trials

    6 – Use AutoML in Azure Databricks

    • What is AutoML?
    • Use AutoML in the Azure Databricks user interface
    • Use code to run an AutoML experiment

    7 – Train deep learning models in Azure Databricks

    • Understand deep learning concepts
    • Train models with PyTorch
    • Distribute PyTorch training with Horovod

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