Come and work with us
Internship Data Science
If you are passionate to work in the field of data science, we have interesting projects for you to work on. We will give you professional experience in the field. If you already know any of Matlab, R or Python languages, it is a plus point. We are here to teach you. So don’t worry. Just send us email with your recent resume.
Bachelor and MS Thesis Projects
We are always looking for students who are interested in ideas for Bachelor and MS thesis. Following learning projects are available
Iris Data Set
This is probably the most versatile, easy and resourceful data set in pattern recognition literature. Nothing could be simpler than iris data set to learn classification techniques. If you are totally new to data science, this is your start line. The data has only 150 rows & 4 columns.
Problem: Predict the flower class based on available attributes.
Titanic Data Set
This is another most quoted data set in global data science community. With several tutorials and help guides, this project should give you enough kick to pursue data science deeper. With healthy mix of variables comprising categories, numbers, text, this data set has enough scope to support crazy ideas! This is a classification problem. The data has 891 rows & 12 columns.
Problem: Predict the survival of passengers in Titanic.
Loan Prediction Data Set
Among all industries, insurance domain has the largest use of analytics & data science methods. This data set would provide you enough taste of working on data sets from insurance companies, what challenges are faced, what strategies are used, which variables influence the outcome etc. This is a classification problem. The data has 615 rows and 13 columns.
Problem: Predict if a loan will get approved or not.
Human Activity Recognition
This data set is collected from recordings of 30 human subjects captured via smartphones enabled with embedded inertial sensors. Many machine learning courses use this data for students practice. It’s your turn now. This is a multi-classification problem. The data set has 10299 rows and 561 columns.
Problem: Predict the activity category of a human