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Asseco Academy » Training » Build machine learning solutions using Azure Databricks

Training DP-3014

Build machine learning solutions using Azure Databricks

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  • Training description
  • Scope

Training description

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..

Prerequisites

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. Consider completing the Create machine learning models learning path before starting this one.

Scope

  • Explore Azure Databricks
    • Introduction
    • Get started with Azure Databricks
    • Identify Azure Databricks workloads
    • Understand key concepts
    • Data governance using Unity Catalog and Microsoft Purview
    • Exercise – Explore Azure Databricks
  • 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
    • Exercise – Use Spark in Azure Databricks
  • 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
    • Exercise – Train a machine learning model in Azure Databricks
  • Use MLflow in Azure Databricks
    • Capabilities of MLflow
    • Run experiments with MLflow
    • Register and serve models with MLflow
    • Exercise – Use MLflow in Azure Databricks
  • Tune hyperparameters in Azure Databricks
    • Optimize hyperparameters with Hyperopt
    • Review Hyperopt trials
    • Scale Hyperopt trials
    • Exercise – Optimize hyperparameters for machine learning in Azure Databricks
  • Use AutoML in Azure Databricks
    • What is AutoML?
    • Use AutoML in the Azure Databricks user interface
    • Use code to run an AutoML experiment
    • Exercise – Use AutoML in Azure Databricks
  • Train deep learning models in Azure Databricks
    • Understand deep learning concepts
    • Train models with PyTorch
    • Distribute PyTorch training with TorchDistributor
    • Exercise – Train deep learning models on Azure Databricks
  • Manage machine learning in production with Azure Databricks
    • Automate your data transformations
    • Explore model development
    • Explore model deployment strategies
    • Explore model versioning and lifecycle management
    • Exercise – Manage a machine learning model
    • Knowledge check
    • Summary

Training schedule

Remote

… if you value the opportunity to learn with a trainer and other participants, from anywhere without having to commute.

Stationary

… if you want to learn while sitting in the same room with the trainer and other participants.

Online

… if you want to learn from materials available via the interenet anywhere at any time

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Build machine learning solutions using Azure Databricks

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Build machine learning solutions using Azure Databricks

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