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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Decision Tree: Concepts- Part 1

A decision tree is one of the main approaches to machine learning. it is a really powerful tool for the aim of Prediction Descriptive analysis and feature selection In this post, I am going to show how decision tree works. In the future posts, I will show you some of the main algorithms for decision tree ...

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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 7)

In the last three parts, I have explained about the time series R custom Visual we have in Power BI. as you remember we have 3 main time series chart in Power BI store (see below): Decompose of time series (trend, seasonality and irregular components). the two other custom visual help us to do forecasting ...

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New Series of Time Series: Power BI Custom Visual (Part 6)

In the last post, I have explained how to do time series forecast using “Exponential Smoothing” approach in Power BI. I start to explain the main parameters that we need to set up. The main concepts behind of most of these parameters have been explained in previous posts (Post 4, Post 3, Post 2, and ...

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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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New Series of Time Series: Part 2 (Exponential Smoothing)

In the last post , I have explained the main concepts behind the timeseries. In this post, I am going to show how we can forecast for some periods. In the last post, I have mentioned that there is a possibility to have “seasonality” “Trend” and  errors (residual) in one dataset: Seasonality+Trend+Residual we call it as ...

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