Pinned Repositories
dc_public_transport
Why DC Metro ridership is declining? Analyzing public transport trends. Various regression models comparison. Tech used: Python Pandas, Numpy, Scipy, Seaborn, Matplotlib.
earthquakes
Visualizing Geo Data of all Earthquakes from the past 7 days. Tech used: Leaflet.js, HTML, CSS, PHP
mars
Flask application with latest Mark data. Tech used: Flask, MongoDB, Splinter, Selenium, Pandas, BeautifulSoup, HTML/CSS, Heroku.
ml_nlp_media
Media bias analysis. Building the predictive model of mass media language using NLP (20 million articles). Tech used: MongoDB, Flask, D3.js, Pickle, Scikit-learn, Plotly, Pandas, Numpy.
project_2ML
Building the predictive model of mass media language using NLP (20 million articles)
springboard
Repository for the Springboard Machine Learning Track work.
sql_playground
SQL playground using Sakila DB. Query building exercise.
usac_e_rate
Universal Service Administrative Company (USAC) E-rate Program Analysis. Tech used: Sodapy, Socrata, Pandas, Numpy, Matplotlib, Seaborn, Plotly Dash.
yegorkryukov's Repositories
yegorkryukov/dc_public_transport
Why DC Metro ridership is declining? Analyzing public transport trends. Various regression models comparison. Tech used: Python Pandas, Numpy, Scipy, Seaborn, Matplotlib.
yegorkryukov/project_2ML
Building the predictive model of mass media language using NLP (20 million articles)
yegorkryukov/springboard
Repository for the Springboard Machine Learning Track work.
yegorkryukov/earthquakes
Visualizing Geo Data of all Earthquakes from the past 7 days. Tech used: Leaflet.js, HTML, CSS, PHP
yegorkryukov/mars
Flask application with latest Mark data. Tech used: Flask, MongoDB, Splinter, Selenium, Pandas, BeautifulSoup, HTML/CSS, Heroku.
yegorkryukov/ml_nlp_media
Media bias analysis. Building the predictive model of mass media language using NLP (20 million articles). Tech used: MongoDB, Flask, D3.js, Pickle, Scikit-learn, Plotly, Pandas, Numpy.
yegorkryukov/sql_playground
SQL playground using Sakila DB. Query building exercise.
yegorkryukov/usac_e_rate
Universal Service Administrative Company (USAC) E-rate Program Analysis. Tech used: Sodapy, Socrata, Pandas, Numpy, Matplotlib, Seaborn, Plotly Dash.
yegorkryukov/bb_dataset
Interactive dashboard to explore the Belly Button Biodiversity DataSet. Tech used: Flask API, Plotly.js.
yegorkryukov/bowling_scorer
yegorkryukov/d3-data-journalism
Looking for demographic information using the 2014 one-year estimates from the U.S. Census Bureau's American Community Survey and 2014 survey data from the Behavioral Risk Factor Surveillance System. Tech used: D3.js, jQuery, Bootstrap
yegorkryukov/delivero
Food ordering app. Tech used: Dart, Flutter.
yegorkryukov/delivero_v2
yegorkryukov/drawing
yegorkryukov/empyrical
Common financial risk and performance metrics. Used by zipline and pyfolio.
yegorkryukov/jobcomparer
yegorkryukov/LSTM-Neural-Network-for-Time-Series-Prediction
LSTM built using Keras Python package to predict time series steps and sequences. Includes sin wave and stock market data
yegorkryukov/pattern_mining
yegorkryukov/projects.online
yegorkryukov/pyfolio
Portfolio and risk analytics in Python
yegorkryukov/python-challenge
GW Data Bootcamp
yegorkryukov/recommenders
Best Practices on Recommendation Systems
yegorkryukov/research_public
Quantitative research and educational materials
yegorkryukov/robintrack
Scrapes the Robinhood API to retrieve + store popularity and price data.
yegorkryukov/staged-recipes
A place to submit conda recipes before they become fully fledged conda-forge feedstocks
yegorkryukov/startbootstrap-new-age
A web app landing page theme created by Start Bootstrap
yegorkryukov/stockai
AI stock market predictor
yegorkryukov/trading_calendars
Calendars for various securities exchanges.
yegorkryukov/twitter_bot
Twitter weather bot. Tech used: Heroku, Tweepy.
yegorkryukov/yegorkryukov.github.io