Qianqian Shan
Qianqian Shan
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Recommender Systems In Practice

10 June 2019 Recommender Systems, Collabarative Filtering, Deep Learning, Auto-Encoders, Restricted Boltzmann Machine, Multi-armed Bandit
This is the documentation of my recommender system project at https://qianqianshan.com/projects/recommender_system/.

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About

Portrait of Qianqian

Resume

My name is Qianqian Shan. I obtained my PhD degree in Statistics from Iowa State University in 2019 under the supervision by Dr. Meeker.

My research interests include Statistical Modeling, Data Analysis, Reliability Analysis, Machine Learning, Deep Learning, Deep Reinforcement Learning and so on. I like coding in Python/C/R/Java and am always excited about learning new knowledge and experienced in independent problem-solving and cross-functional teamwork with three years’ industrial internship and full-time experience.

For my life outside work,I'm a big fan of Yoga, outdoor running, and (entry level) snowboarding. I also have two cats: a naughty Munchkin boy and a very smart Scottish fold girl.

To learn more about me, you may check:

  • https://qianqianshan.com/projects for the projects I have done.
  • https://qianqianshan.com/posts for the posts I have written.
  • Always feel free to reach out via any way listed in Contact or leave me a message.

Experience


Amazon

Applied Scientist • Seattle, WA • Jan 2020 - Present

  • Research and implement machine learning and statistical techniques to create scalable and effective models to improve customer experience.
  • Deep data analysis to solve business problems and to identify business opportunities to provide the best experience on Amazon-owned sites.
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Wells Fargo & Company

Quantitative Intern • Charlotte, NC • May 2019 - August 2019

  • Implemented automated model screening tools in Python to improve modeling efficiency on risk management.
  • Performed stress testing analysis on loan portfolio with statistical and machine learning techniques.
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After, Inc

R&D Remote Part-Time Intern • Norwalk, CT • January 2017 - August 2018

  • Built models for warranty prediction on various products from outdoor sporting equipment to vehicles.
  • Developed reproducible production code with detailed documentation for general use on different projects.
  • Provided consultation advice for clients on premium of warranty products, anomaly detection and other insights that would help their business.
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Education

Iowa State University

PhD in Statistics • Ames, IA • August 2015 - December 2019

  • Student Travel Award in Quality and Productivity Section, Joint Statistical Meetings, Vancouver, BC, Canada.
  • Best Poster Award in Conference on Predictive Inference and Its Applications, Ames, IA, USA.
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Coursera Online Education

Motivated Self-Learner • Ames, IA • January 2013 - Present

  • Deep learning specialization by deeplearning.ai:
    • Neural Networks and Deep Learning (100.00/100.00)
    • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (100.00/100.00)
    • Structuring Machine Learning Projects (100.00/100.00)
    • Convolutional Neural Networks (100.00/100.00)
    • Sequence Models (100.00/100.00)
  • Programming for Everybody (Getting Started with Python) by University of Michigan (100.00/100.00)
  • Python Data Structures by University of Michigan (100.00/100.00)
  • Using Python to Access Web Data by University of Michigan (100.00/100.00)
  • Using Databases with Python by University of Michigan (100.00/100.00)
  • R Programming by Johns Hopkins University (99.20/100.00)
  • The Data Scientist’s Toolbox by Johns Hopkins University (100.00/100.00)
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Udemy Online Education

Motivated Self-Learner • Ames, IA • June 2018 - Present

  • Data Science: Natural Language Processing (NLP) in Python
  • Recommender Systems and Deep Learning in Python
  • Automate the Boring Stuff with Python Programming
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Udacity Online Education

Motivated Self-Learner • Ames, IA • January 2018 - Present

  • Introduction to TensorFlow for Deep Learning by Tensorflow
  • A/B Testing by Google
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Contact

  • qianqianshan.am@gmail.com
  • Qianqian on Github
  • Qianqian on LinkedIn
  • Qianqian on Facebook


Address:
Seattle, WA, USA

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