Madina Zhaksylyk's Projects
Statements rated by user study participants after interaction with a system
Full-stack data analysis to build an interactive dashboard exploring the Belly Button Biodiversity Dataset Using JS, HTML, Plotly and Flask.
Develop a plan for constructing an ETL pipeline for Amazon Review datasets, focusing on two specific datasets: Amazon Japan and Amazon Kitchenware. Assess each dataset to evaluate the reliability of Amazon's Vine program.
This project is based on the ETL process. Extract: original data from two different sources. Transform: data cleaning, joining, filtering, and aggregating. Load: the final database, tables/collections, and why this was chosen.
Excel-Challenge: Kickstart My Chart dataset
This project utilizes leaflet, Javascript and D3 to visualize the earthquake data from the United States Geological Survey (USGS).
This project utilizes leaflet, Javascript and D3 to visualize the earthquake data from the United States Geological Survey (USGS).
This respository apply a Python Matplotlib to visualize real-world pharmaceutical data. The data is sourced from Pymaceuticals Inc., a burgeoning pharmaceutical company based out of San Diego.
The project uses machine learning to predict the likelihood of finding meteorites and will create a web app to provide users with the information. It will also analyze population density, land area, and land coverage to identify areas with potentially unfound meteorites.
HTML Web scraping on Mars data to create a flask web application using Python, Bootstrap, and MongoDB.
This project analyzes opioid overdose data from the United States for all states for the year range including 2013 and 2022.
This repository brings a python pandas solution in the education sector to analyze the city's school district data. This project will help the school board and mayor to make strategic decisions regarding future school budgets and priorities.
This repository brings a python solution for real-life situations. The situations encompass financial, election, human resources, and linguistic research data.
Creating a Python script to visualize the weather of 500+ cities across the world of varying distance from the equator. The idea is to create a representative model of weather across world cities.
Importing CSV files into a SQL database, and then working with those data.
Climate analysis and data exploration of a climate database. Analysis is done using Python Pandas, Matplotlib and SQLAlchemy. API for querying climate data is built using Flask.
I used lending data to create machine learning models that classify the risk level of given loans. Specifically, I compared the performance of the Logistic Regression model and the Random Forest Classifier.
This project analyzes car accident data from the United States in 2020 and 2021 in an attempt to identify possible relationships with various factors. The data used was primarily contained within a csv file found on Kaggle called "US Accidents (2016-2021)", as well as through API calls to the Census API.
VBA-Challenge to make a Stock market Analysis.
Web design using HTML, CSS, and Bootstrap and deployed through Github pages to display climate results from climate data analysis from prior Python-Api-Challenge.
This project analyzes top vacation cities based on weather data from Open Weather's API and is visualized using Google Map's API.