Helen Zheng's repositories
flask_e2e_project
A combination of the tools and services we learned this semester.
docker_flask_homework
This assignment aims to provide hands-on experience in Dockerizing Flask applications, first individually and then using Docker Compose for managing multiple applications.
datasci_9_data_prep
Focus on selecting datasets suitable for a machine learning experiment, with an emphasis on data cleaning, encoding, and transformation steps necessary to prepare the data.
flask_7_auth
Delving into the core of application security: user sessions and authentication. Utilizing Flask and an external identity provider like Google Cloud, ensure your Hospital Priceline application is both user-friendly and secure.
datasci_7_geospatial
Gain hands-on experience with geospatial data processing and visualization using the GCP Maps API and Geopandas. Understand the fundamentals of geocoding, reverse geocoding, and geospatial data visualization in Python.
datasci_6_regression
Get hands-on experience with regression analysis, understanding its principles, and applying it to real-world datasets to predict outcomes and understand relationships between variables.
flask_6_api_management
The goal of this week's assignment is to develop and document APIs using Flask, and manage them with Azure API Management.
flask_5_tailwind
This assignment will give you hands-on experience in video hosting, creating a Flask app styled with Tailwind CSS, and deploying it to a cloud platform. You'll leverage CDN services in Google Cloud or Azure to optimize video delivery, ensuring a seamless user experience for viewers worldwide.
504_class
this is a repo for class
cloud_db_mgmt_pooling_migrations
Gain practical experience in managing a cloud-based MySQL database with a focus on implementing connection pooling and performing database migrations. You will work with both Azure and Google Cloud Platform (GCP) for this assignment.
datasci_6_anova
Gain hands-on experience with ANOVA analysis, understanding its assumptions, and applying it to real-world datasets to understand differences among group means.
datasci_5_statistics
Dive deep into inferential statistics and understand its relevance in drawing conclusions from data. Apply statistical tests to derive insights and make decisions based on data samples.
flask_4_databases_mysql_vm
Manually setting up and running a database on a cloud VM. You'll get hands-on experience setting up a MySQL instance on a VM, integrating it with a Flask app.
mysql_cloudmanaged_databases
This assignment focuses on MySQL, and exploring its implementation on leading cloud platforms: Azure and GCP. By the end, you'll gain hands-on experience in setting up MySQL on these platforms, using MySQL Workbench to design, manage, and interact with your databases, and optionally connecting to your database using Python to retrieve data.
datasci_4_web_viz
Explore web-based platforms for interactive data visualization, contrasting R's Shiny with Python's equivalents. Harness these tools to present data in interactive and user-friendly ways.
sqlite_database_operations
Introduction to the world of databases, starting with SQLite. Integrate data processing with Python, utilize Pandas for exploratory data analysis, and conduct database operations using SQLite.
datasci_3b_visualization
Harness the power of Python visualization libraries, Seaborn and Plotly, to create informative and aesthetically pleasing visualizations. Understand how to select the appropriate visualization technique for various types of data.
datasci_3_eda
Engage in the critical phase of Exploratory Data Analysis (EDA) using the tools and techniques from Python to uncover patterns, spot anomalies, test hypotheses, and identify the main structures of your dataset.
azure_flask_deployment
Hands-on experience setting up a Flask application, integrate it with data processing via Pandas, and deploy the app on Azure App Service. Check Screenshots folder to see the deployment.
datasci_2_manipulation
Delve deeper into data manipulation using Python's prominent libraries. Explore the functionalities of Pandas and get a glimpse of alternatives like Polars, Dask, and Modin.
datasci_1_loading
This is an assignment for HHA 507 to familiarize yourself with Jupyter Notebook (Google Colab) and practice data acquisition techniques
azure_intro_assessment
This is an assignment for HHA 504 to view the Microsoft Azure cloud platform, its core services, and basic integration points with Python
health-analytics
this is a primer assignment for HHA 504/507
gitignore-env
this is an example repo of using a .gitignore and .env file
hha_506_class9
this is a test repo as another example
github-intro
this is an example repo for HHA 506
temp-icd-api-mn
this is a temp project for mn data, related to icd codes