Prediction Model in Azure Notebooks using Python: a Sample Project by Microsoft

As I mentioned in Post, Azure Notebooks is combination of the Jupyter Notebook and Azure. There is a possibility to run your own python, R and F# code on Azure Notebook. In post series, I will share my experience working with Azure Notebook. First, in this post, I will share my first experience of working with Read more about Prediction Model in Azure Notebooks using Python: a Sample Project by Microsoft[…]

Azure Machine Learning Services : Deploy AutoML Model and Use it in Power BI- Part 3

  As I have discussed in part 1 and Part 2, the new possibility of creating machine learning without writing any Python or R codes is so amazing. In Part One, the difference between Azure ML Studio (the traditional one) and the Azure ML Services (new component) has been very briefly explained. (I will write Read more about Azure Machine Learning Services : Deploy AutoML Model and Use it in Power BI- Part 3[…]

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 Read more about Azure Machine Learning Services : Introduction – Part 1[…]

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[…]

R Chart into SSRS (ggplot2 package in SQL Server 2017)-Part 2

“In the last post, you have seen how we can create a chart by importing data from SQL Server 2017. By doing this, we have a reliable code for drawing chart. Now, we sure our codes work fine, we can put the codes in SQL Server 2017. In this post, I am going to show Read more about R Chart into SSRS (ggplot2 package in SQL Server 2017)-Part 2[…]

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[…]

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[…]

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 Read more about Decision Tree: Power BI- Part 2[…]

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 Read more about Azure ML workbench-Data Wrangling -Part 3[…]

Azure ML workbench- Installation-Part 1

In Microsoft ignite 2017, Azure ML team announce new on-premises tools for doing machine learning. this tools much more comprehensive as it provides 1- a workspace helps data wrangling 2- Data Visualization 3-Easy to deploy 4-Support Python codes in this post and next posts, I will share my experiment with working this tools. first I got Read more about Azure ML workbench- Installation-Part 1[…]