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 Read more about Create Custom Visual with R and JSON- Part 4[…]

Create Custom Visual with R and JSON- Part3

In this post, I am going to show you how we can create most comprehensive Custom visual. In the last two posts published in July 2017 (post1 and Post 2). Some notes before I am going to complete the last two posts. 1- We able to declare some custom input like X, Y, Legen and Read more about Create Custom Visual with R and JSON- Part3[…]

Road Map to use Microsoft ML tools

I normally work with most of the Microsoft tools for the aim of doing machine learning. I came up with a roadmap that shows what option for machine learning we have with Microsoft tools in Data Platform. this roadmap is not completed yet, I need to update it one later with some tools such azure Read more about Road Map to use Microsoft ML tools[…]

Run R codes in Azure ML

  There is a possibility to run R codes and Python in Azure ML.  In this short post, I am going to show you how we can run an R codes to show some charts in Azure ML with ggplot2 package. I have a dataset about the dairy product in the USA. this dataset holds Read more about Run R codes in Azure ML[…]

Azure ML Package-Part1

Azure ML Package is another Microsoft related package that allows you to upload and download datasets to and from AzureML, to interrogate experiments, to publish R functions as AzureML web services, and to run R data through existing web services and retrieve the output. Azure ML in R studio The first step- Installation First, you need Read more about Azure ML Package-Part1[…]

Microsoft SQl Server ML Services: RevoScaleR Package

  RevoScaleR Package RevoScaleR is packages created by Revolution Analytics (own by Microsoft) with the aim of importing, transforming, and analyzing data at scale. There are different categories of functions for the data store, imports and save as, data transformation, draw some charts such as histogram, line and so forth, descriptive analysis, predictive analysis, package Read more about Microsoft SQl Server ML Services: RevoScaleR Package[…]

Data Wrangling in Power Query

Before machine learning, we need to go through two main processes: Data preparation and Data wrangling. Data preparation is about the collecting data from resources, integrate and load data in one resource, that is so like ETL (extract, transform, and load process) [2]. According to [2], Data wrangling is when we loaded the data and Read more about Data Wrangling in Power Query[…]

Business Understanding for Machine Learning – Predictive and Prescriptive Analysis

  In the last Post, the explanation about machine learning and what is descriptive analysis has been provided. In this post, I am going to provide some overview of the Predictive and Prescriptive analysis Predictive Analysis Another analysis in machine learning in predictive analysis. Predictive analysis is about supervised learning. That means we want to Read more about Business Understanding for Machine Learning – Predictive and Prescriptive Analysis[…]

Difinity Conference

  I normally post about machine learning topics. this post is mainly about the conference that we organized in February 2018. What is Difinity Difinity Name: Data +Infinity Difinity Location: Auckland, New Zealand When normally Happen: February Difinity Conference: Is a Microsoft Data Platform Conference in New Zealand, Auckland that has been held in 2017 Read more about Difinity Conference[…]

Business Understanding for Machine Learning – Descriptive Analysis

Business Understanding Business understanding is the main and first step for doing machine learning in any platform or languages. Not all business problem can be addressed by machine learning approaches. There are some proposed categories for machine learning such as “Supervised Learning” and “Un-Supervised Learning”. Supervised Learning is about when we identify both input and Read more about Business Understanding for Machine Learning – Descriptive Analysis[…]