Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data, and apply knowledge and actionable insights from data across a broad range of application domains(Wikipedia). We identify relevant questions and use different data collection and analysis programs to translate the outcome of our studies into solutions.
The dataset about cardiovascular diseases which has several attributes such as age, gender, height, weight, blood pressure types, cholesterol, glucose, smoking, alcohol, physical activity and finally cardiovascular disease will be analyzed. In this study, effects of smoking and alcohol consumption on cardiovascular disease with the hypothesis about the age attribute. For this study, some data statistical methods will be applied. Firstly, projection methods which are Principal Component Analysis (PCA), Multi-Dimensional Scaling (MDS), Isomaps, Local Linear Embedding will be applied on dataset and after that Hierarchical Clustering, K-Means Clustering and PAM Clustering will be performed and finally, Internal and External Validation will be carried out.
In different networks and services users have the ability to rate and share their comments on movies, series or shows that they have watched. The feedback given by the users helps the service provider to know which kinds of movies perform better than others in a given demographic. This allows the service provider to improve their offerings. In this project we will make a movie recommendation system that displays certain kinds of movies to a user depending on how they rated the movies they previously watched or depending on what other similar users have previously watched and rated. This will allow the service provider to order different movies for different users more accurately for the goal of creating satisfied customers.