Hi! I am Luke.
Welcome to my website :)

"Machine learning or deep learning? None, I just keep learning"
-- Luke Qi



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About Me

Hi, this is Luke Qi!

I am currently finishing my Master’s of Science in Data Science(MSDS) at University of San Francisco, where I have developed a strong programming and data warehouse skills and become passionate about applying machine learning methods to solve business problems.

Prior to that, I graduated with a BS in Statistics and a BA in Mathematics at University of Minnesota - Twin Cities, where I built a solid knowledge of statistics and mathematics, and realized the how powerful data could be in decision making.

As a Data Scientist Intern at Ubisoft, I am responsible for helping the marketing team boost revenue and optimize pricing strategy by using predictive machine learning model to analyze users' behavior.

The followings are some of my projects that I completed so far that I have been interested in.

Click "more" for details and source code on github.

Featured Projects

Model Evaluation Library

A python package that generates detailed machine learning model evaluation metrics which are useful in industry

(Author, Maintainer, 178 stars and 31 forks)

Monetizer Prediction

A end-to-end machine learning model pipeline in game industry to predict monetizers.

(Python, SQL, Hive, Pipeline, Giraffez)

Customer Transcation Prediction

Predict Santander customer transcation in the future with stacked boosting models. Rank 44/9038 on Kaggle Competition.

(Python, Pipeline, Augmentation, Stacking)

Machine Learning / Statistics

Bankruptcy Rate Prediction

Time Series forecast of Canadian bankruptcy rate with macroeconomic indicator.

(R, Holt-Winters, SARIMA, VARX)

Bike Share Prediction

A neural network built from scratch to predict the bike share at WA D.C.

(Python, DNN, Hyperparameter Tuning)

Wine Quality Classification

White wine quality classification using ensemble machine learning models.

(Python, Resampling, Imbalanced Data)

ETL Pipeline / Cloud Computing

Car Traffic Accident Severity Prediction

Leverage ML algorithms through ETL Pipeline to predict Single-Vehicle Traffic Accident Severity.

(AWS, Spark, MongoDB, s3)

Sentiment Analysis of Movie Review

A web app which interacts with a RNN model performing sentiment analysis on movie reviews.

(SageMaker, RNN, Model Deployment)

User Purchase Prediction in next 7 and 14 days

Leverage ML models through pipeline to process large-scale data to classify purchased user.

(Python, GCP, AWS, Big Data)

Deep Learning

Dog/Cat Image Classification

A web app to classify real-world, user-supplied dog/cat/human images.

(Pytorch, ResNet50, VGG16, CNN)

Seinfeld TV Scripts Generation

A LSTM model to generate my own Seinfeld TV scripts.

(Pytorch, RNN, LSTM, Embedding)

Human Face Image Generation

A DCGAN model to generate new images of faces that look as realistic as possible.

(Pytorch, GAN, Convolutional Layer)

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