Quantum Machine Learning with Python: Using Cirq from Google Research and IBM Qiskit

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Editorial ‏ : ‎ Apress; 1ª edición. (13 Marzo 2021)
Idioma ‏ : ‎ Inglés
Tapa blanda ‏ : ‎ 384 páginas
ISBN-10 ‏ : ‎ 1484265211
ISBN-13 ‏ : ‎ 978-1484265215
Dimensiones ‏ : ‎ 7.01 x 0.87 x 10 pulgadas

Quantum Machine Learning with Python: Using Cirq from Google Research and IBM Qiskit

In recent years, the field of quantum computing has gained significant attention due to its potential to revolutionize various industries, including machine learning. Quantum machine learning combines the power of quantum computing with traditional machine learning techniques to solve complex problems more efficiently.

Two popular tools for quantum machine learning are Cirq from Google Research and IBM Qiskit. Cirq is an open-source quantum computing framework that allows researchers to create, edit, and simulate quantum circuits in Python. On the other hand, Qiskit is an open-source quantum computing software development kit that provides tools for writing quantum algorithms using Python.

To get started with quantum machine learning using Cirq and Qiskit, you can follow these steps:

1. Install Cirq and Qiskit libraries in your Python environment using pip:

   
   pip install cirq<br />
   pip install qiskit<br />
   ```<br />
   <br />

2. Create a quantum circuit using Cirq or Qiskit to perform a quantum machine learning task. For example, you can create a quantum circuit to implement a quantum support vector machine or a quantum neural network.
3. Simulate the quantum circuit using Cirq or Qiskit to understand the behavior of the quantum system and optimize the parameters of the quantum algorithm.
4. Run the quantum circuit on a real quantum device provided by Google or IBM to test the performance of the quantum machine learning model in a real-world setting.

   By using Cirq from Google Research and IBM Qiskit, you can explore the exciting field of quantum machine learning and leverage the power of quantum computing to solve complex problems more efficiently. Start experimenting with quantum machine learning today and unlock the potential of quantum computing for your machine learning projects.

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