Machine Learning & A.I.
You can build in vision algorithms, predictive models, speech processing, and even more modern functionality for your applications. There's everything you could possibly require in order to build a smarter app when you use .NET. This includes the integration of AI and machine learning for cloud and on-device situations.
You can build-in vision algorithms, predictive models, speech processing, and even more modern functionality for your applications. There's everything you could possibly require in order to build a smarter app when you use .NET. This includes the integration of AI and machine learning for cloud and on-device situations. You can use existing models with Cognitive Services, Core ML for Xamarin, or make and use your own models that are built with Azure Machine Learning, TensorFlow, CNTK, and Accord.NET. These technologies will be covered in more details. You can also use MNIST for ML beginners model (Helloworld for Machine Learning) code - think of code built in C# using Tensors or CNTK.
F# for .NET Machine Learning and Data Science:
F# runs on .NET and supports object-focused programming, so it's a highly functional programming language. The type system and offers of features like Units of Measure and Type Providers make it a fantastic option for programming in machine learning and data science.
It's now easy for you to add extensive modern features to .NET Machine Learning applications, either it's vision and speech recognition, understanding of language, knowledge, sentiment detection, or intelligent searching. It has never been easier to infuse your applications, chatbots, and websites with clever algorithms which let them really understand the needs of your users by using natural communicative methods. AI really can bring your business into the future.
Vision: Algorithms for image-processing can identify and moderate images, and give them captions too.
Speech: Audio can be converted into text and your apps can use voice for verification and even offer speaker recognition.
Knowledge: Your apps can map a variety of complex information and data to make tasks like intelligent recommendations and semantic search more easy.
Search: Bing Search APIs can be added to your apps so that they can check a massive number of web pages, videos, images, and more with just one API call.
Language: You can let your apps learn to process natural language and sentiment so they can understand what your users need with the help of pre-built scripts.
Azure Machine Learning:
Azure Machine Learning provides a totally managed cloud service which lets you build, deploy, and share effective predictive analytics solutions. Azure offers scalable and flexible AI development which spans the cloud and the edge.
Services offered by Azure Machine Learning:
• Big data-scaled machine learning
• Container-based AI deployment from the cloud to the edge
• Rapid, scale-out, collaborative experimentation
• Data wrangling powered by AI
• Spark, Cognitive Toolkit, TensorFlow, Caffe Docker, and more
Azure Machine Learning Studio:
• Drag-and-drop development which is serverless
• Code-free, simple experimentation
• Ability to deploy web services in just minutes
Data Science Virtual Machine:
• Pre-configured environments for data scientists
• Sleek and effective integration with Azure services
• Any Virtual Machine size, horizontal scale-out with Azure Batch, and burst compute
• Good support for popular DNN frameworks and GPUs
• User extensibility