Machine Learning (ML) is a branch of both Artificial Intelligence (AI) and computer science. It focusses on the use of data and algorithms to mimic the way that humans learn, gradually improving its accuracy over time.
Microsoft Azure Machine Learning
With Machine Learning, it is possible to become more competitive within your industry or at least maintain competitiveness. Many organisations either fail to get started with Machine Learning or fail to deploy it successfully when they first start. However, solutions like Microsoft Azure Machine Learning provide a platform that can support a successful move into taking advantage of AI and ML.
Building on top of a platform that supports the full life cycle of Machine Learning – where you can build and train models and then move on to scale the solution, all while ensuring that the models you build support both responsible and ethical guidelines, is an effective way to ensure Machine Learning success.
Build and train
The Microsoft Azure Machine Learning platform allows data scientists and developers to build via the Unified Studio Interface. It also supports Open Source frameworks such as Chainer (https://chainer.org/) and MXNET (https://mxnet.apache.org/). With such features as “Automated UI” and “Designer drag and drop,” it allows your developers to build ML based solutions quicker and subsequently roll them out into a production environment at pace.
If flexibility and security are concerns, you can always run the ML on-premise rather than online. If you’re looking to adopt a hybrid approach – whether that be online within Microsoft Azure or with another cloud platform – that’s also possible with Microsoft Azure Machine Learning.
SharePoint Syntex
Whereas Microsoft Azure Machine Learning is aimed at the most sophisticated implementation of Machine Learning, SharePoint Syntax is focused on “the most use day to day” which is typically documents. SharePoint Syntax is a Microsoft 365 service that uses AI to organize and manage content, automate content processing, optimise search and compliance, and transform content into knowledge.
How it works
SharePoint Syntax uses advanced AI more specifically than Machine Learning, along with human intervention, and has the ability to process large amounts of content in small amounts of time, thus enabling what would be forgotten knowledge into usable and actionable information.
The main parts of SharePoint Syntex are:
- understanding the content,
- processing that content and then
- applying compliance to that content.
Understanding
We try to understand the content uses in order to create models that capture, classify and extract information automatically and also apply metadata. This is done with no code. Artificial Intelligence models work with Microsoft Syntax and teach it how to read the content in the way an expert does. Then you’re able to improve the content and its metadata information within that content which will then improve the ability for people to find clear, relevant information and valuable insights.
Processing
Processing is all about capturing the data ingestion followed by its categorisation. Although the most valuable part of SharePoint Syntex is its ability to capture data that is unstructured, it can also work on semi-structured data, such as forms. When integrated, SharePoint Syntex becomes so much more powerful. Integrating it with Microsoft 365 applications, such as Power Automate, allows organisations to better leverage the information extracted from documents
Compliance
It is more than likely that once information is extracted from documents that has previously been hidden, there will be a need to apply some sort of compliance against these documents. With this in mind, Microsoft has made it easy to apply sensitivity and retention labels to documents where specific information has been found. For example, applying a sensitivity label to a document where SharePoint Syntex has found Personal Identifiable Information (PII).
Summary
Although many people are getting excited about Artificial Intelligence and Machine Learning, there is a lot to it in order to take full advantage of the power it offers. You may require a whole new team within your organisation or outsource that work in order to be successful. However, Microsoft makes it easier for the information worker to get started with Machine Learning through SharePoint syntax.
Want to learn more about Machine Learning and how it can help yor organisation? Contact the team at Qaixen to talk to us about the pros and cons of Machine Learning and where to start. Call 08447 724936 or email info@qaixen.com.