B

B.GunaSekhar

Vizianagaram, IN

Intermediate

NARAYANA JUNIOR COLLEGE (MPC)

Feb 2021 - Present

About

A highly motivated and results-oriented professional with excellent communication, teamwork and interpersonal skills. Skilled in problem-solving. Fluent in English and Telugu (native).Enjoys outdoor games such as Cricket and Kabaddi.

Education

NARAYANA JUNIOR COLLEGE (MPC)

2021 - Present

Intermediate in Mpc

February 2021 - Present

is tough and I want to showcase my educational achievements effectively. My educational details are as follows: 1. Bachelor of Science in Computer Science, XYZ University (2015-2019) - Achieved a strong foundation in computer science theories and principles. - Developed expertise in various programming languages such as Java, C++, and Python. - Actively participated in group projects, enhancing collaboration and problem-solving abilities. - Led a team of four in designing and developing a web application, resulting in a 20% increase in user engagement. - Earned a GPA of 3.8, demonstrating consistent academic excellence. 2. Master of Business Administration, ABC Business School (2019-2021) - Specialized in Marketing, honing skills in market research, branding, and strategic planning. - Applied theoretical knowledge to real-world scenarios through case studies and simulations. - Utilized data analytics to identify market trends and make informed marketing decisions. - Led a team of six in a marketing campaign for a local startup, resulting in a 15% increase in sales within six months. - Graduated within the top 5% of the class, showcasing dedication and ability to excel in a competitive environment. By effectively highlighting the impact and action verbs in my education details, I am confident that my resume will stand out amongst the competition and impress potential employers.

Projects

fake news detection using machine learning

Mar 2022 - Jun 2022

. • Developed a machine learning model using classifier techniques to classify text from a dataset as real or fake. • Identified relevant features from the dataset to train the model. • Utilized appropriate metrics to evaluate the model’s performance. • Optimized the model by tuning the hyperparameters. • Implemented various classifier techniques like Logistic Regression, K-Nearest Neighbors, Naive Bayes and Random Forests. • Compared the accuracy of the various models to select the most accurate one. • Partitioned the dataset into training and testing sets to ensure better accuracy. • Visualized the data to analyze the correlations between features. • Analyzed the results of the machine learning model. • Developed a well-documented code for the project.

Awards & achievements

cloud computing

Apr 2023

soft skills

Apr 2023

python

Oct 2022

PCAP: Programming Essentials in Python

Apr 2022

EAMCET RANK

Sep 2020