In this video, I present to you my simple Hybrid (Quantum-Classical) Machine Learning Project titled "Binary Image Classification with Fashion MNIST using TensorFlow Quantum and Cirq". The tools used for the project are TensorFlow Quantum and Cirq (by Google).
Prerequisites:
1. Python
2. Basic Understanding of Classical Machine Learning
3. Familiarity with TensorFlow
If you are not familiar with TensorFlow, have a look at the following video by Edureka
https://youtu.be/AACPaoDsd50
Github link:
https://github.com/Jayshah25/Classification-on-Fashion-MNIST-with-TensorFlow-TensorFlow-Quantum-and-Cirq
Timestamp:
00:00 - Teaser
00:30 - Introduction
07:33 - Installation
13:08 - Dataset
19:09 - Dataset Preprocessing
37:02 - Data Encoding - Part 1
50:32 - Introduction to Quantum Circuit
01:00:32 - Introduction to Cirq
01:08:49 - Data Encoding - Part 2
01:16:55 - Quantum Neural Network
01:36:43 - Results
01:42:45 - What Next?
References
TensorFlow Quantum Official Tutorials - https://www.tensorflow.org/quantum/tutorials/mnist
Cirq Official Tutorials - https://quantumai.google/cirq/tutorials
Paper by Farhi et al - https://arxiv.org/pdf/1802.06002.pdf
Paper by Dmitri Maslov - https://www.google.com/urlsa=t&source=web&rct=j&url=https://arxiv.org/pdf/1603.07678&ved=2ahUKEwi86KbBlfvuAhUmzDgGHfteCIsQFjAJegQIHhAC&usg=AOvVaw04beRgWLMZhYBV6GpyygHF
Intro:
IBM Qiskit Gif (provided to all attendees of QGSS21) converted to video
Music by John_Sib from Pixabay
Cover:
Cirq Image - https://quantumai.google/site-assets/images/marketing/icons/shared-ic-cirq.png
TensorFlow Quantum Image - https://www.tensorflow.org/site-assets/images/project-logos/tensorflow-quantum-logo-social.png