Azure Machine Learning Services : Automated Machine Learning -Part 2

In the last post, what is Azure ML Studio and Azure ML Services has been explained briefly. In this post, I will explain how to use Automated machine learning service. Automated machine learning (automated ML) picks an algorithm and hyperparameters for you and generates a model ready for deployment. Automated machine learning helps to identify ...

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Image and Activity Processing Application with Cognitive Service, Power Apps and Microsoft Flow

There are lots of possibilities to embed cognitive services API in application like Power apps with help of Microsoft flow in the last posts, I have shown how to create Face Recognition application or How to create an OCR application to convert image to text. Face Recognition Application with Power Apps, Microsoft Flow and Cognitive ...

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Azure Machine Learning Services : Introduction – Part 1

  In this post series, I am going to show how we can use Azure Machine learning services and the new features added that make life so easy to train, deploy, automate managing machine learning models [1]. In this post, first I will show how to use a no code environment for Auto ML, how ...

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Export data from Power Query to Local Machine or SQL Server using R scripts

There is always a discussion on how to store back the data from Power BI to local computer or SQL Server Databases, in this short blog, I will show how to do it by writing R scripts inside Power Query.   First how to Store Files to PC To store data back to a file ...

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AI in Dataflow, Azure ML Studio Integration with Power BI Services – Part 3

  In the last two parts, first how we able to use cognitive service in Power BI service (Data flow) has been explained. Then in the second one, the process of using a Pre-built machine learning model for prediction ( classification, regression, and forecasting) has been explained. In this post, I am going to show ...

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Image Processing- Invoice recording using Power App, Microsoft Flow and Cognitive Service- Part 3

  In the last two posts (Post1 and Post2), the process of how to set up a simple Power Apps for the aim of converting the image to text has been explained. The created Power Apps capture a picture from a receipt or any text.  Also, how to create a flow that received the image ...

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Live Machine Learning in Azure Stream Analytics-part 1

Azure Stream Analytics is an event-processing engine that allows users to analyze high volumes of data streaming from devices, sensors, and applications. Azure Stream Analytics can be used for Internet of Things (IoT) real-time analytics, remote monitoring and data inventory controls. However, Azure Stream Analytics is another component in Azure, that we were able to ...

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Azure data Bricks – Part2

In the last post, I have explained how to work with Azure Databricks. In this post, I will show: 1- Upload data in Azure data Lake Store 2- get data from Azure Data Lake Store into Azure Data Bricks 3-clean Data with Scala language 4- visualizes with R language 5- Predictive Analysis with R In ...

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R In Azure Data Lake- Part1- Sample Data

Azure Data Lake store is one of the components in Microsoft cloud, that helps the developers, data scientists and analyst to store any data size, shape, and speed. Azure Data Lake is optimized for processing large amounts of data; it provides parallel processing with optimum performance. In Azure data lake we can create hierarchy data ...

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Create Custom Visual with R and JSON- Part 4

In the last Post, I have explained some parts of creating Custom visual such as how to create an icon, name of visual, and the how-to allocates fields to a custom visual. There are some other settings that need to be set up beforehand as well. the number of data fields you able to pass to ...

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