Creating Machine learning Development and Production Environment in Power BI-Part2

In the last post, I have explained how we can create a function with the aim of parametrising the machine learning process. In this post, I am going to explain how we able to create a Development and Production environment. Create Different Environment in Power Query to create a new environment, In power query, I ...

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Python Programming-Environment

Python is one of the famous programming languages and it is so common for Machine Learning. It is a multi-purpose language that has been leveraged with the aim of device programming, object-oriented programming, machine learning and so forth. In this post, I will introduce some of the common Python IDE programming environment for the aim of ...

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Decision Tree: Power BI- Part 2

In the last Part, I have talked about the main concepts behind the Decision Tree. In this post, I will show how to use decision tree component in Power BI with the aim of Predictive analysis in the report. in next post, I will explain how to fetch the data in Power Query to get a dynamic ...

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Azure ML workbench-Data Wrangling -Part 3

In the last posts, I have explained how to install Azure ML workbench and how to run a sample and check the accuracy. In this post, I am going to show how to do data wrangling using Azure ML workbench. Just click on the left menu, on the database icon. There are 2 separate groups ...

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Time series Series with Power BI- Forecast with Arima-Part 12

In the last posts (Series of Time Series), I have explained about what is ARIMA, what is d,p, and q in ARIMA (p,d,q). In this post, I will talk about how to use ARIMA for forecasting and how to handle the seasonality parameters. in the last example for the age of death of the England king, ...

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Time series Series with Power BI- Arima Model-Part 11

In the last post, I have explained the d value for model ARIMA (p,d,q). In this post, I am going to show how to identify the p and q values as below. one of the main difference between exponential smoothing and Arima is that Arima considers the correlation of a value at a time with ...

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New Series of Time Series: Power BI Custom Visual (Part 5)

In previous posts, I have explained some basic concepts of time series. In the first post I have explained the basic concepts of time series, and in second and third posts I have explained: “Exponential Smoothing” for forecasting data without trend, and with the trend. In the last post, I have explained how we can ...

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New Series of Time Series: Power BI Custom Visual (Part 4)

In this post, I am going to show how we can do time series inside Power BI using custom visual from Office store. First you need to download custom visual from office store, to download R custom visual please follow the below link https://store.office.com/en-001/appshome.aspx?ui=en-US&rs=en-001&ad=US&clickedfilter=OfficeProductFilter%3aPowerBI&productgroup=PowerBI   now we are going to download some timeseries custom visuals ...

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New Series of Time Series: Part 3 (Holt’s Exponential Smoothing)

In the last posts, I have explained the main concepts behind the Timeseries (Post 1) and  in the second one a simple forecasting approach name as “Exponential Smoothing” has been proposed Post 2. In this post I am going to show how to do see the error of forecasting and also how to forecast when ...

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