An Introduction to Quantum Natural Language Processing – Free Udemy Courses
Explore the Emerging Field of Quantum Natural Language Processing (NLP) with lambeq QNLP Toolkit
What you’ll learn
An Introduction to Quantum Natural Language Processing – Free Udemy Courses
- Learn the fundamentals of Quantum Machine Learning (QML)
- Get the basics of Diagrammatic Quantum Theory
- Explore the topic of Quantum Natural Language Processing (NLP)
- Learn about the Distributional Compositional Categorical (DisCoCat) QNLP algorithm
- Explore and learn the usage of lambeq: World’s first High-level QNLP Toolkit
- Gain familiarity with potential applications of NLP and its future research directions
Requirements
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Experience with Python programming language
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Experience with Quantum Computing and IBM Qiskit platform
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Basic familiarity with Machine Learning and Quantum Machine Learning
Description
Quantum Natural Language Processing (NLP) is an emerging field that is at an intersection of Categorical Quantum Mechanics (CQM) and Computational Linguistics. This is one of the unique fields that combine Quantum Computing with Natural Language Processing to take advantage of the properties which the Quantum Computing paradigm provides. NLP is quantum-native which means that the language structure wants to run itself on a quantum computer rather than a classical computer because a natural model of language is equivalent to a natural model utilized to describe quantum mechanical phenomena!
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The only prominent company which is working in the field of NLP is Quantinuum (formerly Cambridge Quantum) which has achieved major milestones in the field of NLP. They were the first to display the true potential of running language on real quantum hardware such as the IBM quantum hardware. They have released the world’s first high-level Python-based QNLP toolkit called lambeq which can convert any diagram (representing the language structure) into a quantum circuit that helps to run the language on quantum hardware and simulator.
This is a short course on Quantum Natural Language Processing giving the primary foundations which will help to get started with NLP and explore its practical applications using the lambeq QNLP toolkit. The course does not provide the mathematical foundations i.e. category theory but rather touches on the diagrammatic quantum theory which is used entirely to build an algorithm (again pictorial) called DisCoCat (Distributional Compositional Categorical).
The course has been divided into the following parts which have a coherent structure to help you navigate according to your requirements:
- Part 1 – Brief Introduction to Quantum Computing
- Part 2 – Basics of Quantum Machine Learning
- Part 3 – Diagrammatic Quantum Theory
- Part 4 – Quantum Natural Language Processing
I am very confident that the field of NLP is developing rapidly and it will take advantage of the quantum computers which we have today just as other applications of quantum computing are taking advantage. The pictorial nature of QNLP concepts is going to attract many to do more research on this unique and amazing field!
Who this course is for:
- Beginners who are curious to know about Quantum Natural Language Processing (NLP)
- Industry professionals & Tech Enthusiasts who want to explore the field of NLP
- Machine Learning, Deep Learning, or AI professionals who want to learn about NLP
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