Email - firstname.lastname@example.org Contact - +91-831******* EDUCATION
B. TECH IN COMPUTER SCIENCE
May 2017 - present Hamirpur, India
College of Engineering
CGPA: 8.15 / 10
Probability and Queuing Models
Computer Graphics + Practicum
Microprocessor and Interfacing
Computer Architecture + Practicum
Object Oriented Programming +
Data Structures and Algorithms +
Operating Systems + Practicum
R • Latex
WEB DEVELOPMENT TOOLS
Flask • HTML • CSS • Bootstrap •
Socket-IO • MySQL
Open Source Software • Jupyter
ACTIVITIES AT ACADEMIC INSTITUTIONS
PARTICIPANT SOFTWARE FREEDOMDAY
September 5th On Campus
• Helped students realise the usefulness of Open Source Software and installed different Linux distros on laptops.
March 2017 NIT Hamirpur
• During our participation the ﬁrst iteration of the hackathon, created a hospital management system with the help of HTML, CSS, PHP and MySQL.
• In the following year, me and my team created a Study Buddy with the help of NodeJS, MongoDB, HTML, CSS, EJS, Socket-IO.
DATA CAPSTONE PROJECT
This project focuses on data analysis and data visualisation on 911 data provided to us. Important python libraries such as Numpy, Pandas, Matplotlib and Seaborn were used to plot and analyse data. Jupyter Notebook was the web application used to write all required code.
ECOMMERCE (WEB VS APP) PROJECT
This project focused on implementing Linear Regression across data to predict some coefﬁcients to solve the given problem. Jupyter notebook was the web application used to write all code and perform necessary actions. The libraries used were Pandas, Numpy, Matplotlib, Seaborn.
TITANIC DATA SET EXPLORATION PROJECT
Titanic data set is a classic example of Logistic Regression and the project focused on implementing machine learning on the given data set and check the accuracy of the solution and compare it with the original data through the use of a confusion matrix. Initial data analysis and visualisation was done with the help of Pandas and Seaborn. K NEAREST NEIGHBOURS ALGORITHM
KNN or K Nearest Neighbours is a unique algorithm that is applied on classiﬁed data, ie: we do not know the origin of the data, no column names, no characteristics, basically we do not know anything about the data given to us, just a series of random numbers, and our goal is to classify the given point. This project was also completed with help of a given unknown data set, and a confusion matrix was used to evaluate our result.
STUDY BUDDY FOR YOUR OWN CAMPUS
Created a project for a hackathon using some common technologies with some of my peers. This project aims to help students ﬁnd all resources on campus and also establish communication with everyone else on campus. The technologies used in this project were, NodeJS, EJS, Mongo DB, Socket-IO, HTML, CSS and Bootstrap.