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IBM Introduces Qiskit Modules for Machine Learning on Quantum Computers


Machine learning technology is usedpractically in all branches of industry, business, science and medicine. The main goal of machine learning is to create conditions under which computers can process large amounts of data. At this stage, the use of quantum computers greatly improves the efficiency of the process.

For successful improvement of algorithm modelsLearning IBM releases Qiskit Machine Learning, an open source application suite of modules for quantum computers that improve the speed and accuracy of machine learning. The involvement of a wide range of developers will allow faster implementation of machine learning on quantum computers, according to IBM experts.

Quantum machine learning (QML) opens up newcapabilities in modeling neural networks and increases the accuracy of these models. Qiskit not only provides high-performance simulators for testing quantum machine learning models on classical computers, but also allows users to test them on real quantum devices, including IBM's publicly available quantum systems.

Practical Applications of Quantum Computingwill allow transferring computer technologies to a qualitatively higher level. New technologies will be implemented in scientific research, when flying into space, developing highly efficient systems for cloud gaming and increasing the speed of the Internet.

Source: medium

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