There is a lot of uproar going on about the influential technologies that are dominating the business Intelligence market for almost every sector. Big data, artificial intelligence, and machine learning are being discovered and analyzed and with passing time people are coming with new applications for a better world and an improved future. While there are some who are still not aware of the potential and capabilities of Machine learning and the value it can add to their business. Machine learning draws insights from raw data and provides solutions to complex business problems based on analysis. Data processing in AI and ml algorithms help computers find hidden insights without any programming or human assistance. It is a technology of the future that ensures heightened efficiency, enhanced customer service relationship, and boosting sales for any business. With big companies like Amazon, Google, and Microsoft bringing in Cloud machine learning platforms, the credibility of artificial intelligence and machine learning just springs up.
There are now several applications of the insights that machine learning draws from raw data. These are used to solve complex business problems, increase efficiency, improve customer relationships, and hike up sales.
NATURAL LANGUAGE PROCESSING
The tech industry just like any other industry faces several challenges from time to time and recently one of them has been the capability for machines to analyze, manipulate, and understand human language. And NLP, a field of machine learning, helps with just that. It gives computers the ability to understand human language by building systems that are able to make sense of text so that they could translate, recommend text, and check grammar. However, certainly there are NLP equipped tools that are used to derive insights that can be used to automate tasks. Algorithms are used to build intelligent systems like voice activated personal assistants - siri, google assistant, alexa, and AI-powered chatbots that are capable of solving issues by translating the language when and where required for machines and humans.
Now when we come to the mechanism on how this works, we will first have to understand the two techniques that go into helping machines understand text. Syntactic analysis that assesses text using basic grammar rules to understand the structuring of sentences. Semantic analysis emphasises on understanding the meaning of the text, first the meaning of individual words and then the meaning when those words are combined.
Business enterprises are getting better at understanding online conversations and how their customers perceive them and their products. They are also able to automate tedious tasks and make them more efficient. Language translation, sentiment analysis, text extraction, topic classification, and chatbots are some of the important applications of NLP known in the technical world. Read More- Get ahead of your competition with Machine Learning
