How To Go From No Math to Quantum Machine Learning

Last updated Aug 10, 2022

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• Status needs revision
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• On quantum computing machine learning

Metadata

• Source:: How To Go From No Math to Quantum Machine Learning - YouTube
• Channel:: Qiskit
• Presenter:: Amira Abbas
• Publish Date:: 2021-06-15
• Review Date:: 2022-03-08

Amira Abbas is living proof that one can go from basically no math to becoming a quantum machine learning researcher. In this video Amira offers specific resources she’s found helpful and also personal tips on the “Do’s and Don’ts” for any pursuing this exciting field. Your formal invite to weekly Qiskit videos ► https://ibm.biz/q-subscribe The Path to QML in Four Steps:  — Math You Need —  Essence of Linear Algebra: https://www.youtube.com/playlist?list… MIT Linear Algebra Course: https://ocw.mit.edu/courses/mathemati… — Getting a Foundation of Machine Learning —  (Book) Deep Learning by Ian Goodfellow, Yoshua Bengio and Aaron Courville: https://www.deeplearningbook.org — Getting a Foundation in Quantum Computing —  (Book) Quantum Computation and Quantum Information by Michael Nielsen and Isaac Chuang: http://mmrc.amss.cas.cn/tlb/201702/W0… EdX Courses: quantum Information Science Part 1-3: https://www.edx.org/course/quantum-in… Qiskit Textbook: https://qiskit.org/textbook — Understanding QML —  (Book) Supervised Learning with Quantum Computers by Maria Schuld and Francesco Petruccione: https://www.springer.com/gp/book/9783…

To figure out a path towards mastering Quantum Machine Learning.

Following are the steps needed to prepare for a career in Quantum Machine Learning, according to Amira:

1. Shaping your mindset
   • It’s not easy but being persistent and positive would go a long way.
2. The Math
   • Quantum Computing and Machine Learning overlap in the mathematics you need.
   • To learn about Linear Algebra, first start off with Essence of linear algebra - YouTube to get a better intuition and to be able to think visually.
   • Then do some Linear Algebra course on Coursera/EdX/MIT etc. like Linear Algebra | Mathematics | MIT OpenCourseWare
3. Get the basics of Machine Learning
   • Start with the Deep Learning book by Ian Goodfellow et al. Deep Learning (deeplearningbook.org)
4. Quantum Computing
   • Start with Quantum Computation and Quantum Information
   • For a more hands-on approach, go with Learn Quantum Computation using Qiskit
   • There are also some great EdX courses as well, like Quantum Information Science I, Part 1 | edX
5. Quantum Machine Learning
   • The recommended book to start-off with is Supervised Learning with Quantum Computers.

Following are some of the tips for embarking on QML journey.

1. Don’t start with research papers.
2. Set your expectations correctly.
   • Quantum Computing is a more theoretical field as of now, and we might not see its practical applications in our generation.
   • If you’re more of a hands-on practical person, then this might not be for you.
   • Know what you’re getting into.
3. The importance of mentorship
   • Having a mentor is really crucial to get into a field and to better understand the topics, as well as to feel motivated.
   • Join a community, either through Slack/Discord channels, or Github Open Source contributions or some other course forum.

• Essence of linear algebra - YouTube
• Linear Algebra | Mathematics | MIT OpenCourseWare
• Deep Learning (deeplearningbook.org)
• Quantum Computation and Quantum Information
• Learn Quantum Computation using Qiskit
• Quantum Information Science I, Part 1 | edX
• Supervised Learning with Quantum Computers