anita-tech Goto Github PK

clustering

K-means clustering

concept

Hypothesis space; Huber Loss

message-board

opencv

Open Source Computer Vision Library

pca

clustering, PCA and K-means clustering

women-in-tech_hrm

About the Project's Topic and the Broad Context There are assumptions made that female engineers are unrepresented in companies operating in the technology sector. This is something that is beneficial to study in length and in various ways. There are several existing studies shared publicly. One of these studies was written by Tara Siegel in 2014. It is the belief of our team that interesting findings can be made by looking at the representation of women in the technology sector of the recent past. These findings - collected in this project - could perhaps one day inspire others to conduct similar studies and by that add to the pool of research made on the topic. Background This project was written by Yongbing Tao-Topinoja, Sejal Seth and Rami Laaksonen. Our three-member team represents diverse nationalities, academic backgrounds and past fields of work. The project forms the team's final project for the Python for Data Analysis training program. The training program was organized by The Shortcut Oy in Helsinki, Finland from February until April 2020.