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title: Visualize data combined from multiple data sources by using Azure Monitor Workbooks
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summary: Use Azure Workbooks to query data from multiple data sources and use visualizations such as graphs, charts, and grids to build visual reports for data analysis and reporting.
title: Working with data and properties in React components
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summary: The goal of React components is to create reusable blocks of code and UI. To support reusability, you can pass data into components through the use of properties. We will see how to add properties to a component, and work with complex data types such as arrays.
summary: Applications typically involve data that will be changed by user interactions. These changes are often managed through some form of state and events. In this module, we explore the concepts of state and events. We also look at the tools React provides for management.
summary: React.js is the most popular front-end JavaScript framework. Through JSX, a combination of HTML and JavaScript, developers are able to create views in a natural fashion. Developers can also create components for reusable blocks across their applications. This learning path will introduce you to React, and the core skills you need as a developer to use this powerful framework.
summary: React.js is the most popular front-end JavaScript framework. Developers use JSX, a combination of HTML and JavaScript, to create views in a natural way. Developers can also create components for blocks that can be reused across their applications. This module introduces React and the core skills developers need to use this powerful framework.
title: Create a mixed reality basketball player lineup with the Mixed Reality Toolkit
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summary: "Use C#, Visual Studio, Unity, and the Mixed Reality Toolkit to create an interactive virtual reality experience compatible with the HoloLens. Inspired by *Space Jam: A New Legacy*, you create an experience for coaches and fans to learn more about the Tune Squad."
title: Create a web app that uses data to make decisions on the basketball court
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summary: "Use JavaScript, Azure, GitHub, and Visual Studio Code to write a web app that helps the Tune Squad coach make data-based decisions on the basketball court, inspired by SPACE JAM: A NEW LEGACY."
title: Predict basketball player efficiency ratings by using machine learning and Visual Studio Code
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summary: "By using anonymized data from real and animated basketball players in the upcoming film *Space Jam: A New Legacy*, create a machine learning model to cleanse data to be used during games. Also explore bimodal data distributions by using Python in Visual Studio Code."
title: "Use basketball stats to optimize game play with Visual Studio Code, inspired by SPACE JAM: A NEW LEGACY"
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summary: "Inspired by the new film _Space Jam: A New Legacy_, this learning path shows basketball fans how an understanding of data science and coding can support their passions, create opportunities, and even open doors to possible careers. Develop skills in Visual Studio Code, Azure, GitHub, JavaScript, and Python, to gain insights into how individual moments throughout a player's history can lead to a critical game decision in the finals."
title: Prepare to bring the basketball court into a Mixed Reality space
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summary: "Discover the fundamentals of Mixed Reality and prepare the resources you need to create an interactive experience for basketball fans and coaches inspired by *Space Jam: A New Legacy*."
title: Train a machine learning model for predictive maintenance by using ML.NET Model Builder
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summary: 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.
title: Introduction to regression models by using R and tidymodels
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summary: Get an introduction to regression models. In machine learning, the goal of regression is to create a model that can predict a numeric, quantifiable value.
title: Introduction to classification models by using R and tidymodels
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summary: Classification is a form of machine learning in which you train a classification model to predict which category an item belongs to. In this module, you learn how to use the R programming language and tidymodels framework to train classification models.
title: Create machine learning models with R and tidymodels
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summary: Learn how to explore and analyze data by using R. Get an introduction to regression models, classification models, and clustering models by using tidymodels and R.
title: Classify endangered bird species with Custom Vision
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summary: As an ornithologist, you study the behavior, physiology, and conservation of birds and bird habitat. Your work often involves surveying, recording, and reporting on bird activity. You want to build a machine learning model that will identify a bird in an image by species, to help with gathering data. In this module, you use Azure AI Custom Vision to create a model to identify species of birds!
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