6 Machine Learning Platforms by Microsoft
5 Best Machine Learning Platforms by Microsoft
This article outlines the structure of a machine learning platform, delving into its specific functions. It encourages readers to consider their requirements and guides them in constructing an effective machine learning platform. In the end, the suggestion is to utilize privately-configured machine learning training platforms, preferably those offered as open source platforms by Microsoft.
Machine learning requires not only data scientists to develop new models, software engineers to apply new models, but also software engineers and operations engineers to build machine learning platforms. Building a machine learning platform is an important part of the enterprise and team that apply machine learning.
#1 Azure Cloud: Microsoft Machine Learning Service:
Azure Cloud, with its years of research and development Microsoft has launched a machine learning cloud platform on this MaaS demand. The platform is “a fully managed cloud service that enables data experts and develop Azure Cloud – Microsoft Machine Learning Services to efficiently embed predictive analytics into their applications helping organizations to use large data sets” At the same time, it provides a complete set of machine learning workflows for data download, model selection, model training and data prediction, and is presented to developers in a very friendly visual interface at each step.
#2 AutoML: Machine Learning Automation:
From a machine learning perspective, AutoML can be seen as a very powerful system for learning and generalizing on given data and tasks. But it emphasizes that it must be very easy to use. From an automation perspective, AutoML can be seen as designing a series of advanced control systems to operate machine learning models so that the model can automatically learn the appropriate parameters and configurations without human intervention. A generic AutoML definition is as follows: generic AutoML .
The core tasks of AutoML:
Better performance, No human assistance Lower computation budgets
#3 Azure Machine Learning Studio:
Azure Machine Learning Studio has a large number of machine learning algorithms that you can now use to build predictive analytics solutions. These algorithms can be used for general machine learning: regression analysis, classification, clustering, and anomaly detection, each of which can solve different types of machine learning problems.
Microsoft Azure’s Machine Learning Algorithm is designed to help you filter the available machine learning algorithms and choose the right one for your predictive analytics solution. Cheat Sheet will ask you these two questions: the nature of the data, the problem you are trying to solve, and then suggest an algorithm you can try.
#4 Microsoft Cognitive Services:
Today, machine learning and artificial intelligence are no longer mysterious black technologies. It is more likely for natural human-computer interaction applications to allow applications to plug in smart wings and make applications Owner’s wisdom. So, below, we will introduce you to our cognitive services, and hope that you can bring intelligence into your application and make your ideas come true.
#5 Microsoft – BoT Framework:
The Microsoft Chat Robot Framework (Bot Framework) allows your service to create and connect AI robots, through which your service can chat freely with users by typing, texting, Skype, Slack, Office 365 mail and other popular services. Wait. Chat bots are fast becoming a part of our digital life, and they have become another important way of interacting with users or services after the web and mobile. Developers writing chatbots face the same problem. For example, robots need basic input and output operations.
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