This repo briefly introduce AI and NLP with a comprehensive overview of Microsoft Azure AI and NLP solutions. It then provides a mapping between NLP applications and Azure AI solutions. The repo also contains the links to the Microsoft official repositories.
For this repository our target audience includes developers, data scientists and machine learning engineers with different levels of NLP knowledge who are seeking an easy guide to try Azure AI/NLP solutions.
Natural Language Processing (NLP) is a field of artificial intelligence, machine learning, and computational linguistics. Its primary goal is the interactions between computers and human (natural) languages including tex and speech.
In particular, NLP provides different techniques of how a computer program can understand, analyse, and potentially generate large volume of human language data.
NLP applications include natural language understanding, machine translation, semantics , the syntactic passing, natural language emulation, dialectal systems such as speech recognition, question & answering and a broad range of text analytics techniques such as topic modelling, classification, summarization, sentence/document similarities etc.
The term AI was coined by American computer scientist John McCarthy at the 1956 Dartmouth Conference, widely considered the birthplace of the discipline. Known as the father of AI, McCarthy created the Lisp computer language in 1958, which became the standard AI programming language and continues to be used today.
The breakthrough in AI -and NLP in particular- happened when Alan Turing, an Englsih mathematian, published his famous article "Computing Machinery and Intelligence" and proposed what is now called the 'Turing test'.
Turing test is used to determine whether or not computer(machine) can think intelligently like human?. This criterion depends on the ability of a computer program to impersonate a human in a real-time written conversation with a human judge, sufficiently well that the judge is unable to distinguish reliably — on the basis of the conversational content alone — between the program and a real human.
Below the AI-timeline is captured at a glance with the breakthroughs of Machine learning, Deep learning and NLP:
The Microsoft AI platform provides a suite of powerful tools to allow developers to easily and quickly infuse AI into their applications and scenarios, enabling new, intelligent experiences for their users.
This is a free-understanding of mapping between Azure AI solutions and NLP applications.
Azure AI offers three different solution types for NLP applications:
These solutions are there APIs, SDKs, and services available to help developers build intelligent applications without having direct AI or data science skills or knowledge. Azure Cognitive Services enable developers to easily add cognitive features into their applications. The goal of Azure Cognitive Services is to help developers create applications that can see, hear, speak, understand, and even begin to reason.The catalog of services within Azure Cognitive Services can be categorized into five main pillars - Vision, Speech, Language, Web Search, and Decision.
Below is the official repositories for some of the services published by Microsoft:
These solutions are designed for advanced knowledge mining tasks, such as Name Entity Recognition, Phrase Extraction, Custom labelling and Custom skills, where can enrich the IE process.
Verseagility is a Python-based toolkit for your custom natural language processing task, allowing you to bring your own data. It is a central component of the Microsoft Services Knowledge Mining offering.
Microsoft research has published a repository contains examples and best practices for building NLP systems, provided as Jupyter notebooks and utility functions. The focus of the repository is on state-of-the-art methods and common scenarios that are popular among researchers and practitioners working on problems involving text and language.
Micorosoft Free NLP learning path including four modules on:
- Analyze text with the Text Analytics service
- Recognize and synthesize speech
- Translate text and speech
- Create a language model with Language Understanding
Dr Lida Ghahremnalou, NLP Specialist and AI/Advanced Analytics Cloud Solution Architect at Microsoft UK.