Interactive Charts using R and Power BI: Create Custom Visual Part 1

I am so excited about using Plotly packages in Power BI. So What is Plotly: is an R package for creating interactive web-based graphs via the open source JavaScript graphing library :https://plot.ly/r/getting-started/ this feature has been added recently and had been announce by Christian Christian Berg in Data insight summit 2017. I started to search about ...

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Speaking Files in Microsoft Data Insight Summit 2017

Microsoft Data insight Summit 2017 has been held in Seattle from 12 to 13 Jun. It is the main conference for Microsoft Data Analysis with Power BI. All interesting and new topics in Power BI has been presented. Most of the speakers are from Microsoft product team or  experienced speakers in this fields. there are ...

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Azure ML Part 9- Cross Validation: Machine Learning Prediction (6)

In the previous posts (from Part 1 to Part7), I have explained the whole process of doing machine learning inside the Azure ML, from import data, data cleaning, feature selection, training models, testing models, and evaluating. In the last post, I have explained one of the main ways of improving the algorithms performance name as “Tune ...

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Azure ML Part 8- Tune Parameters: Machine Learning Prediction (5)

In the previous posts from Part 1 to 7, I have explained how to do machine learning with Azure ML. I have explained some of the main components in Azure ML that helps us to do data wrangling, train the model, feature selection and evaluating the result. The data cleaning such as SQL transformation, select ...

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Azure ML Part 7: A Machine Learning Prediction scenario (4)

In the previous posts from Part 1 to 6, I have explained how to do machine learning process. The data cleaning such as SQL transformation, select specific columns, remove missing values,  Edit meta data, and normalize data.  Also, I have explained how to find relevant attributes  using Feature Selection Feature to identify which feature are more ...

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Azure ML Part 4: A Machine Learning Prediction scenario (1)

In previous Posts Part 1, Part 2 and Part3  I have explain some about the azure Ml environment, how to import data into it and finally how to do data transformation using Azure ML component. In this post and the next one I am going to show how to do a Machine Learning in Azure ...

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K-mean clustering In R, writing R codes inside Power BI: Part 6

In the previous post,I have explained the main concepts and process behind the K-mean clustering algorithm. Now I am going to use this algorithm for classifying my Fitbit data in power BI.   as I have explained in part 5, I gathered theses data from Fitbit application and I am going to cluster them using ...

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Over fitting and Under fitting in Machine Learning

The main aim of machine learning is to learn from past data that able us to predict the future and upcoming data. It is so important that chosen algorithm able to mimic the actual behaviour of data. in the all different machine learning algorithms, there is away to enhance the prediction by better learning from ...

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Have more Charts by writing R codes inside Power BI: Part 3

In the previous parts (Part 1 and Part 2) , I have shown how to draw a chart in the power BI (Part 1) visualization. Also, in Part 2 I have shown how to present 5 different variables in just one single chart. In this post, I will show how to shows some sub plots in a ...

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Azure Machine Learning Part 3: Data Transformation in R

In previous post I have explained how to import data into Azure ML environment. In this part,I will show how to do data cleaning, data transformation in Azure ML environment. The second step in machine learning process is bout collecting (Part 2), cleaning and loading data (current part). Azure ML has different components for data ...

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