Open source quantum machine learning tools

When quantum physics and algorithms started to be integrated into machine learning tools, a whole new era of data science began. While machine learning algorithms are used to compute immense quantities of data, quantum machine learning utilizes qubits and quantum operations or specialized quantum systems to improve computational speed and data storage done by algorithms in a program.

If you are looking forward to experimenting with this new technology, there are some open source tools available.

Braket

Amazon’s fully managed quantum computing service for building quantum algorithms.

Framework for creating, editing, and invoking Noisy Intermediate Scale Quantum (NISQ) circuits.

Rigetti’s software library for writing, simulating, compiling and executing quantum programs.

D-Wave System’s suite of tools for solving hard problems with quantum computers.

Compiler framework with algorithm libraries, optimizer, scheduler, QEC, mapping, micro-code generator.

All these tools are, as we mentioned before, open source tools that are available free of charge.

If you want to know more about machine learning and its derivatives, and how you can take advantage of these technologies, we can talk about it. Contact us!

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