Susie Xia's repositories
AI_music_Heroku
Deploy app of Music Classification with CNN models
School_District_Analysis
Use Python and Pandas library to analyze school district data and showcase trends in school performance based on key metrics.
SF_Employee_Comp_Dash
Practice in plotly/dash with python
BigData_Amazon_reviews_ETL_Cloud
Performing cloud-base ETL and analyzing data using SQL, Natural Language Processing (NLP) pipeline and Machine Learning model.
Cryptocurrencies
Unsupervised Machine Learning, clustering data using K-means algorithm
Mapping_Earthquakes
Traverse and retrieve GeoJSON data to populate a geographical map using JavaScript, D3, mapbox API and leaflet libraries.
NeuralNetwork_Charity_Donation
Create a deep-learning neural network to analyze and classify the success of charitable donations.
Plotly_Webpage
Deploying an interactive dashboard using Plotly.js to explore data on the biodiversity of belly buttons.
Alogrithm_python
Practice algorithms in Python
bikesharing
Creating Tableau from NYC Citi Bike
GreenEnergy_VBA
Using VBA and Excel Macro to analyze the performance of green energy stocks
Mission-to-Mars
Web scraping to extract live data about the Mission to Mars. Storing and updating it in MongoDB, and then rendering the data in a web application created with Flask.
Movies-ETL
Automated ETL(Extract, Transform and Load) Pipeline.
Pewlett-Hackard-Analysis
Build employee Database with PostgreSQL by using data modeling, engineering and analysis
PyBer_Analysis
using Python, Pandas and Matplotlib to analyze and visualize data with Jupyter Note Book.
Python_Election_Analysis
Python project for analyzing Election results
Supervised_Machine_Learning
Supervised ML models
surfs_up
Using Python, SQLAlchemy, and Flask, analyze and visualize climate data before open a surf shop.
TensorFlow_Practice
Performing several Neural Network by using TensorFlow python library
Unsupervised-ML-models
Practice of several unsupervised Machine Learning Models
World_Weather_Analysis
Collect and analyze weather data to recommend ideal hotels based on clients’ weather preferences.