Quantum Machine Learning: Tools and Techniques

Quantum computing is accelerating its power into the IT field to revolutionize artificial intelligence (AI) and machine learning (ML) to get bigger and better results than standard computing without these technologies. Traditional computers will continue to serve their daily purposes but with the help of quantum machine learning. QML has the potential to revolutionize many industries if applied properly with the use of appropriate tools and techniques.

In today’s exclusive newsletter, we will learn about the QML tools and techniques that will help you perform difficult computing tasks within a few clicks.

Open-Source Quantum Software Projects

Most of the quantum computers are large and also quite expensive. However, there is another alternative, which is cloud-based quantum machine learning platforms that provide the maximum features that quantum computers might have. Here is a curated list of open-source quantum software projects available on GitHub:

1. PennyLane from Xanadu

PennyLane is a Xanadu software product for programming quantum computers that uses a cross-platform Python library for quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations. PerryLane is an interesting piece of software as it supports Xanadu’s continuous various photonic technology along with plug-ins to support gates, which can be found in ProjectQ and IBM’s Qiskit.

2. Paddle Quantum

Paddle Quantum is a popular QML tool based on Baidu’s flying paddle that supports the structure and training of quantum neural networks (QNN) and provides easy-to-use QML development kits for quantum optimization, quantum chemistry, and other cutting-edge quantum application toolsets.

3. TensorFlow Quantum

TensorFlow Quantum (TFQ) is a quantum machine learning library provided by Google that is known for rapid prototyping of hybrid quantum-classical ML models. The software focuses on quantum data and building hybrid quantum classification models that integrate quantum computing algorithms and logic designed in Cirq.

The growing awareness of the quantum of ML has allowed industries to explore more about this technology, which will help businesses in the future fight problems effectively. These tools are just another way to help you explore and understand the importance of QML in your business.

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