Pinned Repositories
awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
Bayesian_propensity_score_matching
A simulation-based framework to compare the robustness againist unobserved heterogeneity effect between Bayesian Propensity Score Matching and traditional Propensity Score Matching
gps_staypoint_detection
GPS data processing
Intersection_peds_bike_demand_model_ongoing
Develop the demand models to predict pedestrian and bike volume for Minneapolis urban intersections. This is an on-going project and the data are confidential.
nlp_text_summarization_implementation
Three modules of extractive text summarization, including implementation of Kmeans clustering using BERT sentence embedding
Pyspark-Stack-Overflow-User-Analysis
Ride-sharing-trip-k-means-and-visualization
Rigorious_safety_performance_function_Bayesian_approach
Safety performance function (SPF) is one of the most important tools in transportation safety study. The SPF is usually estimated in the frequentist framework. In this study, Bayesian models were used to address the heterogeneity issues.
tf_image_classification_cifar10
WebApp_New_York_visitor_volume_prediction
NYC check-in prediction
lingyu001's Repositories
lingyu001/nlp_text_summarization_implementation
Three modules of extractive text summarization, including implementation of Kmeans clustering using BERT sentence embedding
lingyu001/gps_staypoint_detection
GPS data processing
lingyu001/Rigorious_safety_performance_function_Bayesian_approach
Safety performance function (SPF) is one of the most important tools in transportation safety study. The SPF is usually estimated in the frequentist framework. In this study, Bayesian models were used to address the heterogeneity issues.
lingyu001/awesome-machine-learning
A curated list of awesome Machine Learning frameworks, libraries and software.
lingyu001/Bayesian_propensity_score_matching
A simulation-based framework to compare the robustness againist unobserved heterogeneity effect between Bayesian Propensity Score Matching and traditional Propensity Score Matching
lingyu001/Intersection_peds_bike_demand_model_ongoing
Develop the demand models to predict pedestrian and bike volume for Minneapolis urban intersections. This is an on-going project and the data are confidential.
lingyu001/Pyspark-Stack-Overflow-User-Analysis
lingyu001/Ride-sharing-trip-k-means-and-visualization
lingyu001/tf_image_classification_cifar10
lingyu001/titanic_LL_solution
Kaggle Titanic Data Challenge (https://www.kaggle.com/c/titanic/), Applied several ML classifiers to predict the survival of passengers.
lingyu001/WebApp_New_York_visitor_volume_prediction
NYC check-in prediction
lingyu001/awesome-public-datasets
A topic-centric list of HQ open datasets. PR ☛☛☛
lingyu001/coursera-test
Coursera test repos
lingyu001/datasharing
The Leek group guide to data sharing
lingyu001/flasked-altair
Tools to build a dashboard/webapp with Flask and Altair! Inspired by Dash.
lingyu001/folium
Python Data. Leaflet.js Maps.
lingyu001/FourSquare_HeatMap_NYC
A heatmap of checkins from Four Square in NYC for 10 months. Dataset taken from Kaggle
lingyu001/github-actions-course-template
project repo for getting start with github actions
lingyu001/github-actions-demo
A demo repo for github actions
lingyu001/HungaBunga
HungaBunga: Brute-Force all sklearn models with all parameters using .fit .predict!
lingyu001/leetcode
👏🏻 leetcode solutions for Humans™
lingyu001/machine_learning_miniprojects
lingyu001/models
Models and examples built with TensorFlow
lingyu001/Predict-Bank-Authentication_A-DNN-Tensorflow-Exercise
lingyu001/prophet
Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.
lingyu001/Recommendation
lingyu001/StatisticsForApplication_solution
lingyu001/TabPy-docker
Tableau Python Server (TabPy) running in docker
lingyu001/tidytuesday
Official repo for the #tidytuesday project
lingyu001/vega-embed
Publish Vega visualizations as embedded web components with interactive parameters.