Machine learning

Comparing models in Azure Machine Learning

November 23, 2020 by Dinesh Asanka

Introduction

After discussing a few algorithms and techniques with Azure Machine Learning let us discuss techniques of comparison in Azure Machine Learning in this article. During this series of articles, we have discussed the basic cleaning techniques, feature selection techniques and Principal component analysis, etc. After discussing Regression and Classification analysis let us focus more on performing comparison in Azure Machine Learning.

Prediction with Classification in Azure Machine Learning

October 30, 2020 by Dinesh Asanka

Introduction

After discussing Regression in the previous article, let us discuss the techniques for Classification in Azure Machine learning in this article. Like regression, classification is also the common prediction technique that is being used in many organizations. Before the regression we have discussed basic cleaning techniques, feature selection techniques and Principal component analysis in previous articles, now we will be looking at data classification techniques in azure machine learning in this article.

Prediction with Regression in Azure Machine Learning

October 6, 2020 by Dinesh Asanka

Introduction

We will be discussing one of the most common prediction technique that is Regression in Azure Machine Learning in this article. After discussing the basic cleaning techniques, feature selection techniques and principal component analysis in previous articles, now we will be looking at a data regression technique in azure machine learning in this article.

Data Reduction Technique: Principal Component Analysis in Azure Machine Learning

August 31, 2020 by Dinesh Asanka

Introduction

We will be discussing one of the most common Data Reduction Technique named Principal Component Analysis in Azure Machine Learning in this article. After discussing the basic cleaning techniques, feature selection techniques in previous articles, now we will be looking at a data reduction technique in this article.

Feature Selection in Azure Machine Learning

August 19, 2020 by Dinesh Asanka

Introduction

After discussing cleansing and prediction aspects in Azure Machine Learning, we will dedicate this article to another important feature, which is Feature Selection in Azure Machine Learning.

Prediction in Azure Machine Learning

July 16, 2020 by Dinesh Asanka

Introduction

After discussing the basic features of Azure Machine Learning and how to clean the data from Azure Machine Learning, let us look at how to perform prediction in Azure Machine Learning. Prediction is one of the important aspects of Machine Learning as it will help to make strategic decisions.

Data Cleansing in Azure Machine Learning

July 2, 2020 by Dinesh Asanka

Introduction

After discussing the basic features of Azure Machine Learning in my previous article, Introduction to Azure Machine Learning using Azure ML Studio, we will look at techniques of data cleansing in Azure Machine Learning. Data Cleansing or Data Cleaning is an important aspect when it comes to predicting as quality data will improve the quality of data prediction.

Introduction to Azure Machine Learning using Azure ML Studio

June 18, 2020 by Dinesh Asanka

Introduction

Let us see how Azure ML studio can be used to create machine learning models and how to consume them in this series. As we discussed during the data mining series, we identified the challenges in the predictions in data. In the Azure Machine learning platform, machine learning workflows can be defined in easy scale models in the cloud environment. Today will be looking at how datasets can be uploaded.

Using Logistic Regression in Azure ML for Predicting Customer’s Loan Eligibility

August 19, 2019 by Ben Richardson

This article aims to provide the basics of creating Logistic Regression in Azure ML by designing a simple model step-by-step.

How to use JSON data in Azure Machine Learning

November 9, 2018 by Esat Erkec

Azure Machine Learning (also known as Azure ML) is cloud-based machine learning solution of Microsoft. Microsoft Azure Machine Learning is a fully-managed cloud-based service that provides the ability to create and train predictive analytic solutions. Another advantage of Azure ML is that you can access and easily make changes anywhere in machine learning models with help of Microsoft Azure Machine Learning Studio.

Machine Learning Services – Configuring R Services in SQL Server

October 25, 2018 by Ben Richardson

The R language is one of the most popular languages for data science, machine learning services and computational statistics. There are several IDEs that allow seamless R development. Owing to the growing popularity of the R language, R services have been included by Microsoft in SQL Server 2016 onwards. In this article, we will briefly review how we can integrate R with SQL Server 2017. We will see the installation process and will also execute the basic R commands in SQL Server 2017.

How to develop a K-Means model on Azure Machine Learning Studio

January 30, 2018 by Esat Erkec

In this article, we will discuss the k-means algorithm and how can we develop a k-means model on Azure Machine Learning Studio.

Machine learning is an area of artificial intelligence that helps us develop relationships between data and predict the future. There are many secrets that are hidden in the data. To discover these secrets, we need Machine Learning algorithms. Machine learning plays the key role in leveraging existing data to exploit business opportunities.

How to integrate SQL Server and Azure Machine Learning

January 11, 2018 by Esat Erkec

Good, clean and reliable data is important for every company, because well-analyzed data will open new possibilities to success. When we look at successful companies, we see that they’ve analyzed customers, sales, and finance data very well. At this point, a game changer enters: machine learning.

Machine learning

Machine learning is a type of artificial intelligence which analyzes data in order to predict future and discover hidden patterns. The output helps us make decisions. Machine learning is widely used in finance, healthcare and marketing.