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new learning and dev tools
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- [Nielsen and Chuang](http://quantum.wobblybit.com/category/nielsenchuang/) - Worked examples on quantum algorithm problems.
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- [QISKit Tutorials](https://github.com/QISKit/qiskit-tutorial) - Jupyter notebooks simply demonstrating how to use QISKit.
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- [Quantum Algorithm Zoo](http://math.nist.gov/quantum/zoo/) - Comprehensive catalog of quantum algorithms.
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- [Quantum Computing Playground](http://www.quantumplayground.net/#/home) - 3D quantum state visualisation tool able to simulate up to 22 qubits.
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- [Quantum in the Cloud] (http://cnotmz.appspot.com/#) - Four qubit photonic quantum simulator and computer.
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- [Quantum Machine Learning for Data Scientists](https://arxiv.org/pdf/1804.10068.pdf) - Explanation of quantum machine learning algorithms.
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- [Quirk](http://algassert.com/quirk) - Browser-based drag-and-drop quantum circuit simulator that reacts, simulates, and animates in real-time.
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## Development Tools
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- [Cirq](https://github.com/quantumlib/Cirq) - Python library for writing, manipulating, and optimizing NISQ circuits to run on quantum computers.
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- [IBM Quantum Composer](https://quantumexperience.ng.bluemix.net/qx/editor) - Online quantum composer to run experiments on real quantum computing hardware.
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- [Microsoft Quantum Development Kit](https://docs.microsoft.com/en-us/quantum/?view=qsharp-preview) - Microsoft Q# programming language.
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- [Project Q](http://projectq.ch/) - Framework for implementing quantum computing in Python.
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- [pyQuil](https://github.com/rigetticomputing/pyquil) - Python library for quantum programming using Quil.
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- [QCL](http://tph.tuwien.ac.at/~oemer/qcl.html) - Older, C like language for quantum computers. Only has a simulator and debugger.
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- [QISKit SDK](https://github.com/QISKit/qiskit-sdk-py) - Software development kit for working with OpenQASM and the IBM Q Experience.
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