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Machine Learning In Laymen's Terms
Machine Learning A Laymans Understanding. Machine learning is considered a subset of Artificial Intelligence, which provides machines with the ability to learn without being explicitly programmed.
A Deep Learning Machine On Azure From The App Marketplace
How to use a pre-configured environment on Azure to create a "ready to go" Deep Learning machine
Social note on Artificial Intelligence
This Article is brief on upcoming AI and trending technologies in the sector. Most important it also consider social impact and psychological tenet of AI
Adult Dataset In Machine Learning Using Azure
In this article, we will see how to create and deploy the simple machine learning Application Adult Data set.
Five Ways In Which Machine Learning Can Impact FinTech
Machine learning is one amongst those technologies that is invariably around us and that we might not even comprehend it. For instance, machine learning is employed to resolve issues like deciding if an email that we got is a spam or a genuine one, how cars can drive on their own, and what product someone is likely to purchase. Every day we tend to see these sorts of machine learning solutions in action. Machine learning is when we get a mail and automatically/mechanically scanned and marked for spam within the spam folder. For the past few years, Google, Tesla, and others have been building self-drive systems that may soon augment or replace the human driver. And data information giants like Google and Amazon can use your search history to predict which things you are looking to shop for and ensure you see adds for those things on each webpage you visit. All this useful and generally annoying and unwanted behavior is the result of artificial intelligence.
House Price Prediction By Using Machine Learning
This article will explain to predict house price by using Logistic Regression of Machine Learning.
Build A Machine Learning Model With ML.NET CLI
In this article, we will learn how to build a Machine Learning model in ML.NET Framework using ML.NET CLI.
How To Choose Machine Learning Algorithms
Learn how to select machine learning algorithms based on data characteristics, accuracy, training time, linearity, and model parameters.
Two-Class Boosted Decision Tree
Two-Class Boosted Decision Tree module creates a machine learning model that is based on the boosted decision trees algorithm. A boosted decision tree is an ensemble learning method in which the second tree corrects for the errors of the first tree, the third tree corrects for the errors of the first and second trees, and so forth. Predictions are based on the entire ensemble of trees together that make the prediction.
Cardiovascular Disease Detection In ASP.NET Core Using ML.NET
Build, train, evaluate, and integrate an ML.NET binary-classification model for cardiovascular disease prediction into an ASP.NET Core MVC application.
Building Recommendation Systems In Python
This article will help you build different types of basic recommendation systems using python.
Getting Started With Machine Learning .NET For Clustering Model
In Build 2018 Microsoft interduce the preview of ML.NET (Machine Learning .NET) which is a cross platform, open source machine learning framework. Yes, now its easy to develop our own Machine Learning application or develop costume module using Machine Learning framework.ML.NET is a machine learning framework which was mainly developed for .NET developers. We can use C# or F# to develop ML.NET applications.ML.NET is an open source which can be run on Windows, Linux and macOS. The ML.NET is still in development and now we can use the preview version to work and play with ML.NET.
Key Machine Learning Terms
In this article, you will learn about the terms used in machine learning technology.
Two Class Support Vector Machine
An overview of Two Class Support Vector Machine. Two-Class Support Vector Machine is used to create a model that is based on the Support Vector Machine Algorithm.
Developing A Recommender Solution With Azure Machine Learning
In this article you will learn how to develop a recommender solution with Azure Machine Learning.
Machine Learning Processes And Scenarios
Machine learning processes and scenarios. Things in machine learning are repeated over and over and hence machine learning is iterative in nature. Therefore, to know machine learning, one has to understand the machine learning process. The machine learning process is a bit tricky and challenging. It is very rare that we find the machine learning process easy.
Introduction To Machine Learning - Part One
Machine learning is a field or a part of computer science that gives the robot or computers the ability to learn without being explicitly programmed.
Credit Card Fraud Detection In ASP.NET Core Using ML.NET
In this article, we'll learn how ML.NET framework is used to build a Credit Card Fraud Detection machine learning solution. Then we will see how to integrate that into ASP.NET Core MVC applications.
How To Do Binary Classification in ASP.Net Core Using ML.Net
In this article, we will see binary classification in ASP.Net Core using ML.Net.
Understanding Machine Learning
Learn the basics of machine learning, including how systems learn from data and the differences between supervised and unsupervised learning.
Introduction To Machine Learning
Introduction To Machine Learning. So, what is machine learning? The one important area where we could apply machine learning is to find patterns in data. Then those patterns are used to predict the future and make decisions.
Challenges In Machine Learning (Training And Validation) - Part Three
This is the last part of the three series article - "Challenges in Machine Learning" that covers manipulating the data to get the best accuracy of the of machine learning model.
Challenges In Machine Learning - Part Two
This article covers major challenges faced in a machine learning project due to bad data.
Microsoft Cognitive Services Leap Forward
New AI APIs from Microsoft give developers a great opportunity
New in Machine Learning - An Intent Based Network Management
Implementation and application of Machine Learning are growing rapidly across different industries. The next big thing is Intent-Based Network or IBN.
Chronic Kidney Disease Prediction In ASP.NET Core Using ML.NET
In this article, we'll learn how ML.NET framework is used to build a Chronic Kidney Disease Prediction machine learning model and integrate them into ASP.NET Core MVC application.
KNN- K-Nearest Neighbors using Python
The k-nearest neighbors (KNN) algorithm is a simple, supervised machine learning algorithm that can be used to solve both classification and regression problems. It's easy to implement and understand but has a major drawback of becoming significantly slower as the size of the data in use grows. In this article, you will learn to implement kNN using python
Multiple Linear Regression using Python
Multiple linear regression (MLR), also known simply as multiple regression, is a statistical technique that uses several explanatory variables to predict the outcome of a response variable. In this article, you will learn how to implement multiple linear regression using Python.
