With the objective to track NBA fan engagement on Twitter to optimize participation and enhance gameplay. The Source of the Study we used for this project is data of 2020 NBA Final Game 5 (9/25/2020)- Miami Heat vs Boston Celtics. The final game result was Celtics won 121–108 being down as much as 12 points in the first quarter.

For complete codes please refer to https://github.com/rachelsung/Sports-Analytics-Sentiment-Analysis

Objective

Nowadays, fans can engage in sports in a multitude of ways such as attending games, watching games through their league related TV subscriptions, enrolling in loyalty programs, or posting online real-time reactions. …


HR Analytics Project with the UPS Case. Data Visualization Tool: Tableau

https://public.tableau.com/profile/chiachi.sung#!/vizhome/HRDashboard_16148973535320/Dashboard1?publish=yes

Company Overview

United Parcel Service, Inc. aka UPS is one of the world’s largest package delivery companies, with over 528,000 employees globally serving more than 220 countries and territories. In 2019, UPS delivered an average of 21.9 million pieces per day and generated a total of $74.1 billion in revenue.

UPS has competitive strengths in its robust global network and the variety of services, such as air, ground, domestic, international, commercial and residential. …


In this project, we will use the data extracted from multiple online retail websites to build the Item Attribute Tool and Outfit Recommendation System by utilizing the Natural Language Processing (NLP) techniques.

The whole project will be separated into 2 parts:

  1. Product Attribution Prediction
  2. Outfit Recommendation

For complete codes please refer to https://github.com/rachelsung/ThreadTogether-Fashion-Item-Classification-and-Recommendation-System

Part 1: Product Attribution Prediction

A. Data Preprocessing

The original datasets contain product information including brand, product name, description, brand category, and product details.

Below are steps we took to process the raw datasets:

a. Combine all columns into one string for further processing.

b. Remove stopwords:

  • Tokenize string we created before and return a…

Rachel Sung

Data story teller. | Linkedin: https://www.linkedin.com/in/rachelsung/

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