KEERTHI CHIRRAPU

Recent graduate with excellent research, technical, and problem-solving skills. Detail-oriented and able to learn new concepts quickly.

Motivated Computer Science student seeking internship to gain hands-on experience. Outgoing and friendly with strong drive to succeed. Highly organized, proactive and punctual with team-oriented mentality. Ambitious, career-focused job seeker, anxious to obtain an entry-level Data analyst position or any developer roles which meets my requirements to help launch career while achieving company goals.

• Certified in a Language Proficiency Test for Employability organized at Anurag Group of Institutions.
• Certified by TCS-ION in Career Edge.
• Certified by Coursera in Python and AI For Everyone.
• Certified for participation at International Conference on Advances in Computational Intelligence and Informatics (ICACII).

• Participated in a Hackathon on Machine Learning by IBM.
• Participated at Pre-Conference Workshop on Machine Learning with Python on IBM cloud.
• Attended an independently organized Ted event at AGI.

• Presented a Mini Project on the implementation of Text Summarization using TF-IDF Algorithm and converting the summarized text into Audio File Using Google Text to Speech API in my Bachelors. File containing text is taken as input from end user and we extracted total text from that file and summarized the text and converted the summarized text into audio file using GTTS API.
• The main objective of text summarization system is to identify the most important information from the given text and present it to the end users.

• Presented a Major project on Startup Success Prediction. We created a predictive model based on machine learning for the purpose of Startup Success Prediction to master a company's success.
• We proposed a method to predict the outcome of a startup based on many key factors like seed funding amount, seed funding time, series a funding, factors contributing to the success and failure of the company at every milestone.
• We used a supervised Machine Learning in which a machine leaning algorithm like DT, KNN, Logistic Regression, Random Forest, XGBoost builds a model by examining many examples and attempting to find a model that minimizes loss.
• Predictive modelling is a statistical technique using machine learning and data mining to predict and entrepreneurs Success prediction likely future outcomes based on the input given by registered user in our application with the aid of historical and existing data based on the dataset end.