dongdyang/interpretable-deep-model-mta

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Python
Created almost 5 years ago
Updated almost 5 years ago

dongdyang/interpretable-deep-model-mta

dongdyang

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This is the project that developed for marketing attribution. It is an interpretable deep learning model for marketing problem.

binary-classification-task-xgboost

binary classification task for Kaggle sample using Pandas, sklearn, xgboost

MASNUM

This is the project to join ASC16 and gain the application innovation prize. The paper URL is http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0169130&type=printable

QA-DSSM

This is knowledge-base Question and Answering system using DSSM method.

Log-Analysis

This is the project using Java Hadoop to analyse system log file in several server to do some statistic jobs.

Wechat-tool-for-USC-Second-hand-Group

This is the original Wechat mini code built for second hand group. The function of it is to transfer message between different group chat. In this way, the people in different groups could keep in contact with each others and the information of second hand things are shared.

deep_learning_multi_touch_attribution_with_interpretation

This is the project that developed for marketing attribution. It is an interpretable deep learning model for marketing problem.

Compiler_buaa

2015_buaa_compiler_extPL0_13061026

DailyProgramming

LeetCode and other trial programs

eShop-via-ROR

This is about e-shop online project, which is an final project about Ruby On Rails. This is a ROR exercise project done in BUAA Ruby course.