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awesome-datascience

:memo: An awesome Data Science repository to learn and apply for real world problems.

bicycling-in-seattle

This research project was aimed towards identifying the factors that inhibit bicycle commuting in Seattle (specifically in and around the University of Washington i.e. University District). - To begin with, we identified five broad categories of factors considered to affect biking, based on literature review and secondary data sources - Infrastructure, Safety, Community Support, Personal Reasons and Environment. - The literature review consisted of several news articles published by the Seattle Times, SDOT (Seattle Department of Transportation) Open Data, SDOT's very own BMP (Bicycle Master Plan), the Commute Seattle survey report published in 2017, and information published by peopleforbikes.org & bikeleague.org. - Based on this framework, we conducted a survey using Qualtrics software to gain further insight into how bicycle riders (active, inactive as well as potential riders) rate the importance of each of these individual factors in their daily commute choices. - To accompany the survey responses, we conducted personal (1:1) semi-structured interviews with interested survey respondents, to gain an in-depth, rich understanding of their concerns and possible suggestions (for improvements) in relation to the current scenario. - A thematic analysis of the interview responses yielded further insight into the probable pain-points for current and potential bicycle riders. - Based on qualitative and quantitative analysis, the findings of this study (aimed at SDOT) were presented in a classroom of 40 graduate students taking the IMT 570 course during Fall quarter (all pursuing their Master's degrees at the iSchool), the presentation was rated best-in-class by the teaching staff. - The final report highlighted key areas for further research and experimentation - that would have the maximum impact in encouraging more Seattleites to take up bicycling as a commute option, whether it is for work or recreation.

ch3-git-basics

Exercises for Chapter 3: Git and GitHub

ch5-functions

Exercises for Chapter 5: Functions

credit-card-fraud-detection

exploring-aws-sagemaker

exploring_gams_for_modeling_data

forecasting-avocado-prices-in-us

health_spending_data_comparison

Comparing estimates for global health spending across 195 countries between IHME and WHO

health_spending_for_oecd_countries

image-classification-using-deep-learning

job-board-platform-analysis

nyc-boro-taxi-tip-predictions

restoration-and-colorization-of-grayscale-memories-using-cnns

Group project

web-scraping-cooking-recipes-for-common-ingredients

yelp-super-user-impacts