I started studying quantum machine learning, but I did not know the entrance to do scientific research paper in this field, knowing that I have a strong background in quantum information theory and dealing with quantum systems, but I have a simple background in machine learning. Where do I start rightly? Is there simple research or a book to start with? What is the appropriate programming language for that?
Thanks
I would drop the pretention about quantum computing , for now at least, not sufficiently developed. Unless you want to study circuitry based on nanostructure devices, there is more physics in that. But its mainly on laboratory level.
On the other hand there is plenty of stuff in digital circuit design with Boolean logic.
Another way you can go is neuronal network simulation on computers for use in AI, there is plenty also on that also.
Your best bet is to try to join a university research group dealing in such matters, then you learn fast.
M. Y. Abd-Rabbou Getting started with quantum machine learning (QML) might be difficult, especially if you are new to machine learning. There are, however, a few things you may do to get started:
1. Learn about the fundamentals of machine learning: Before getting into QML, it's critical to grasp the fundamentals of machine learning. Begin by learning about common machine learning algorithms including supervised learning, unsupervised learning, and reinforcement learning. There are several online courses and introductory books available to assist you get started with machine learning.
2. Learn about quantum computing: Because QML is built on quantum computing, it's critical to grasp the fundamentals of quantum computing, such as quantum gates, quantum states, and quantum entanglement. Many online courses and introductory books on quantum computing are available to help you get started.
3. Learn a quantum computing programming language: Before you can begin exploring with QML, you must first learn a quantum computing programming language. Python, C++, and Julia are the most common quantum computing languages. To get started with these languages, you can utilize software libraries like Qiskit, PyQuil, or Cirq.
4. Begin with easy research: There are numerous research papers and publications in QML, but starting with the most recent and difficult works might be daunting. To begin, read easy and introductory papers on the subject to become acquainted with the field and its present status.
5. Books: "Quantum Machine Learning: What Quantum Computing Means to Data Mining" by Peter Wittek, "Quantum Computing Explained" by David McMahon, and "Quantum Machine Learning: An Introduction" by Maria Schuld et al. are all good places to start.
6. Online lessons and workshops: There are several online tutorials and workshops available to assist you get started with QML. The IBM Q Experience, the Quantum Computing Playground, and the Quantum Information Science Kit are all prominent online tools.
Remember that mastering QML will require time and effort, but it is an intriguing and quickly expanding field with the potential to transform machine learning.
Juan Weisz Thanks for the important information and for your valuable suggestion. I am really looking forward to joining a research team on this interesting topic.
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