This repository contains my personal Data science projects which helped me to get experience using Python and relevant data science and machine learning libraries such as Pandas, Numpy, Seaborn, Matplotlib, Scikit-Learn, TensorFlow, Keras etc.
Bike-sharing systems are a new generation of traditional bike rentals where the whole process from membership, rental and return back has become automatic. Through these systems, the user is able to easily rent a bike from a particular position and return back to another place. Currently, there are over 500 bike-sharing programs around the world which are composed of over 500 thousand bicycles. Today, there exists great interest in these systems due to their essential role in traffic, environmental and health issues.
Apart from interesting real-world applications of bike-sharing systems, the characteristics of data being generated by these systems make them attractive for research. Unlike other transport services such as bus or subway, the duration of travel, departure and arrival position is explicitly recorded in these systems. This feature turns the sharing system into a virtual sensor network that can be used for sensing mobility in the city. Hence, it is expected that the most important events in the city could be detected by monitoring these data.
Bike-sharing rental process is highly correlated to the environmental and seasonal settings. For instance, weather conditions, precipitation, day of week, season, hour of the day, etc. can affect the rental behaviors.
- Regression --> Predication of bike rental count daily based on the environmental and seasonal settings.
- Event and Anomaly Detection --> The Count of rented bikes are also correlated to some events in the town which easily are traceable via search engines. For instance, a query like "2012-10-30 washington d.c." in Google returns related results to Hurricane Sandy.
- Weather 1: Clear, Few clouds, Partly cloudy, Partly cloudy
- Weather 2: Mist + Cloudy, Mist + Broken clouds, Mist + Few clouds, Mist
- Weather 3: Light Snow, Light Rain + Thunderstorm + Scattered clouds, Light Rain + Scattered clouds
The dataset related to the two-year historical log corresponding to the years 2011 and 2012 from the Capital Bikeshare system, Washington D.C., USA which is publicly available at http://capitalbikeshare.com/system-data. We aggregated the data on two hourly and daily basis and then extracted and added the corresponding weather and seasonal information. Weather information is extracted from http://www.freemeteo.com. The data is retrieved from: Fanaee-T, Hadi, and Gama, Joao, "Event labeling combining ensemble detectors and background knowledge", Progress in Artificial Intelligence (2013): pp. 1-15, Springer Berlin Heidelberg, doi:10.1007/s13748-013-0040-3.
The project applies a Deep-learning algorithm to recognise whether the patient has caught Covid or not given the X-ray image. The algorithm used for image classification is a Convolutional Neural Network (CNN) and the specific model is the VGG19.
