Showing 13321–13332 of 14641 results
Train compute-intensive models with Azure Machine Learning
Large-scale machine-learning and deep-learning models require ample compute power. Learn when to choose GPU compute, and how different frameworks help you to make optimal use of GPU compute during preprocessing, model training, and deployment.
Train deep learning models in Azure Databricks
Deep learning uses neural networks to train highly effective machine learning models for complex forecasting, computer vision, natural language processing, and other AI workloads.
Train models in Azure Machine Learning with the CLI (v2)
The Azure Machine Learning CLI (v2) is an Azure CLI extension that you can use to train and deploy machine learning models. Learn how to use the CLI (v2) to create Azure Machine Learning workspace assets to use for model training and deployment.
Train models with scripts in Azure Machine Learning
To prepare your machine learning workloads for production, you'll work with scripts. Learn how to train models with scripts in Azure Machine Learning.
Train-The-Trainer
Create and deliver engaging workshops in this course.
Transactions and Error Handling in PostgreSQL
Ensure data consistency by learning how to use transactions and handle errors in concurrent environments.
Transactions and Error Handling in SQL Server
Learn to write scripts that will catch and handle errors and control for multiple operations happening at once.
Transfer and transform data with Azure Synapse Analytics pipelines
Azure Synapse Analytics enables data integration through the use of pipelines, which you can use to automate and orchestrate data transfer and transformation activities.
Transfer Learning: Tailoring Neural Networks for Your Data
Transfer learning is one of the core concepts leveraged for building Generative AI applications. This course teaches the essentials of transfer learning as well as advanced strategies such as fine-tuning and feature extraction.
Transferring Data with ETL
This course covers creating and orchestrating ETL pipelines using the industry’s best practices and tools: Python, SQL, Apache Spark, and Apache Airflow.
Transferring Data with ETL
This course covers creating and orchestrating ETL pipelines using the industry’s best practices and tools: Python, SQL, Apache Spark, and Apache Airflow.
Transform business software authoring with fusion development teams
Do you want to empower your development team to build better apps, faster? Maybe you want your development teams to work more efficiently with and deliver more value to your business teams. Or you want to free business, or citizen, developers to create applications for their ever changing needs. Ultimately you want your software development, IT, and business teams to work better together; a new software development paradigm called Fusion Development teams can help.