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Serena's Projects

ccl-asl icon ccl-asl

Python Module for parsing Apple ASL Logs

courses icon courses

Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1

intro-to-data-science-in-python icon intro-to-data-science-in-python

Repo for the first course of the Applied Data Science with Python Specialization taught by University of Michigan hosted by Coursera

manim icon manim

Animation engine for explanatory math videos

sales-data-prediction-system icon sales-data-prediction-system

The specific problem in this project is about the time-series data trend prediction. The specific application scenario is in e-commerce. You are given a real dataset obtained from a real-world e-commerce application where there were 1000 products and 31490 customers (i.e., buyers) who bought these products. Of these 1000 products there are 100 key products (popular products). Also these 1000 products are in 15 categories. The specific data are given in the seven tables and the specific details of these tables are given below. The time window of this dataset is in 118 days with data documentation for each day. Hence, the time unit is one day where the timeline goes from the 0-th day to the 117-th day (17 weeks less one day in total). Now you are asked to do the sale quantity prediction for the 100 key products for each day between the 118-th day and the 146-th day (29 days).

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