Real world data analysis using Quantum Machine Learning algorithms

[ManjulaGandhi]

Description

Aim of our project is to build hands-on tutorials for implementing quantum machine learning algorithms with real world data sets using Qiskit. This tutorial should give learners a taste of what QML is really about. We are planning to work with various QML techniques such as Quantum Naive Bayes, Quantum k-nearest neighbor methods, Quantum Support Vector Machine and Quantum Bayesian networks.

We will be working on some of the real datasets for Prediction of student learning outcomes, Prediction of rising global surface temperature and Prediction of credit card fraud detection.

Deliverables

Output will be in the form of jupyter notebooks and journal paper.

Mentors details

Name: Dr. Manjula Gandhi.S GitHubID: ManjulaGandhi What they do: Associate Professor (Computer Science Faculty), Coimbatore Institute of Technology

Name: Balaji Seetharaman GitHubID: bala-ceg What they do: Software Engineer at Extreme Networks and Final year Master’s student at BITS Pilani

Number of mentees

2

Type of mentees

• Mentee

• Required

  • Proficiency in classical machine learning
  • Good working knowledge in python, jupyter notebook

• Nice to have

  • Good writing skills

[bala-ceg]

I am excited and looking forward to collaborating with Professor @ManjulaGandhi for this Project

[iotaisolutions]

Interested

[Mit-byte]

Interested

[EACMichiels]

Could I still joint this team ? I would love to ! Eric.

[bala-ceg]

Checkpoint 1 presentation

#18 Real world data analysis using Quantum Machine Learning Algorithms_checkpoint1.pdf

[HuangJunye]

@Mit-byte @KakashiOO7 Can you please comment in the issue so that I can assign you? Thank you.

[KakashiOO7]

Sure @HuangJunye .

[Mit-byte]

👍 @HuangJunye

[bala-ceg]

Checkpoint 2 work update & visual update

Work Update.pdf

https://user-images.githubusercontent.com/70808619/166948780-10d201ab-6f27-4877-a23e-e64cb9eca5e0.mp4

[KakashiOO7]

Final Showcase:

Video Link