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Trademark and Trademark Law: protect your logo, design, tag line and more…
Learn about trademark Search & Protect Your Name, tagline, Logo, Design, Brand & Be the Market Leader!
Traditional Compute Options
This course covers the fundamentals of traditional compute options in the IBM Cloud® Platform.
Train a machine learning model for predictive maintenance by using ML.NET Model Builder
Train a machine learning model in Visual Studio with ML.NET by using Model Builder, which uses sensor data to detect whether a manufacturing device is broken.
Train a machine learning model in Azure Databricks
Machine learning involves using data to train a predictive model. Azure Databricks support multiple commonly used machine learning frameworks that you can use to train models.
Train and evaluate classification models
Classification is a kind of machine learning used to categorize items into classes.
Train and evaluate clustering models
Clustering is a type of machine learning that is used to group similar items into clusters.
Train and evaluate deep learning models
Deep learning is an advanced form of machine learning that emulates the way the human brain learns through networks of connected neurons.
Train and evaluate regression models
Regression is a commonly used kind of machine learning for predicting numeric values.
Train and manage a machine learning model with Azure Machine Learning
To train a machine learning model with Azure Machine Learning, you need to make data available and configure the necessary compute. After training your model and tracking model metrics with MLflow, you can decide to deploy your model to an online endpoint for real-time predictions. Throughout this learning path, you explore how to set up your Azure Machine Learning workspace, after which you train and manage a machine learning model.
Train and track machine learning models with MLflow in Microsoft Fabric
In Microsoft Fabric, data scientists can train models in notebooks, track their work in experiments, and manage their models with MLflow.
Train and understand regression models in machine learning
Regression is arguably the most widely used machine learning technique, commonly underlying scientific discoveries, business planning, and stock market analytics. This learning material takes a dive into some common regression analyses, both simple and more complex, and provides some insight on how to assess model performance.
Train compute-intensive models with Azure Machine Learning
Train compute-intensive models with GPU compute in Azure Machine Learning. By monitoring workloads, you can find the optimal compute configuration. Distributed training allows you to train on multiple nodes to speed up training time.