Hello,

I am Divya

Full Stack Dev|

About

Hello, I'm Sai Sri Divya Dasari, a dedicated programmer from Amalapuram, Andhra Pradesh, India. I hold a Bachelor's degree in Computer Science and Engineering from Rajiv Gandhi University of Knowledge and Technologies, Srikakulam with CGPA 8.5. I'm passionate about self-development and continually seek opportunities to enhance my skills. My expertise spans various programming languages, including C, Python, Machine Learning, Data Science, Artificial Intelligence, Frontend, and Backend Technologies. Recently, I completed a 6 Months of internship as a Full Stack Developer specializing in Machine Learning and Artificial Intelligence

Open Source Contributor

I have completed my bachelor's degree (B.Tech) in Computer Science at Srikakulam, Andhra Pradesh.

  • Degree: Bachelor of Technology in Computer Science
  • Current Status: Looking for Job

My interests are in Software Development , Machine Learning, Data Science,Generative AI, Travelling , Community Development, etc. I love to explore new technologies.

Projects

I developed few projects during my academics for learning purposes, and I listed some of them below. You can visit my GitHub to see more such projects

Voice Enabled Chatbot Project

Technologies used: Open AI, LLM , vector databases, Hugging face, HTML, CSS, JS, Bootstrap
Leveraged the power of large language models to generate human-like text responses, enabling natural and engaging conversations with users. Integrated OpenAI's API to access cutting-edge language generation capabilities, enhancing the chatbot's conversational abilities and creativity. Leveraged Gradio and Hugging Face's pre-trained models and libraries to fine-tune and optimize the chatbot's performance, ensuring it met specific project requirements.

Source Code

Smart Presentation Control By Hand Gestures

Technologies Used: Media Pipe, Open CV, Hand Gesture Recoginization Library
The smart presentation control system developed using hand gestures, implemented through Python and computer vision techniques, represents a significant advancement in human- computer interaction, particularly in the context of presentations. Its accessibility, affordability, accuracy, and automation capabilities position it as a valuable tool for presenters seeking innovative ways to engage with their content and captivate their audiences

Source Code

Kidney Stone and Tumour Prediction

Harnessing Convolutional Neural Networks for accurate medical imaging analysis. Cutting-edge technology for early detection and personalized healthcare.Inputs may include:Demographic data (age, gender, family history), Medical history (previous stones, underlying conditions),Laboratory results (urine pH, calcium levels),Imaging findings (stone size, location)
- Machine learning algorithms analyze these inputs to predict:Stone recurrence risk,Stone growth rate,Response to treatment

Source Code

Rice leaf Disease Detection Using CNN

Technologies Used: Convolutional neural networks, Data science operations, Machine learning models
Utilized CNN for disease classification: Leaf Blast, Brown-spot, Bacterial Leaf Blight, and Leaf Scald. Achieved train accuracy of 99% and test accuracy of 96.24%, demonstrating strong predictive performance.

Source Code

Colourization Of Black And White Images

Colorization of black and white images is a fascinating process that transforms grayscale images into vibrant, colored versions. By imbuing monochromatic pictures with a spectrum of hues, this technique breathes new life into historical photographs

Source Code

Rainfall Prediction Using Flask

Rainfall prediction combines the power of machine learning, specifically the CatBoost algorithm with Flask. This application allows users to predict rainfall based on various input features and provides a experience for obtaining predictions.

Source Code

Hand Written Digits Recognizatoin Using Gradio

Handwritten Digit Recognition using Gradio: Employs Gradio's interactive UI to showcase a Convolutional Neural Network (CNN model accurately identifying handwritten digits. Intuitive, real-time recognition for diverse applications Source Code

Twitter Sentiment Analysis

The power of Natural Language Processing on Twitter data to discern sentiments. This project employs advanced algorithms to analyze and categorize social media sentiments, offering valuable insights into public opinions and trends. Source Code

More Projects

Portfolio

  • Internships
  • Certifications

Virtual Internship On Web Development

Frontend Development Intern

Resume

Education

Bachelor's of Technology in Computer Science

2020 - 2024

Rajiv Gandhi University Of Knowlodge And Technologies, Srikakulam, AP

Currently in my Final year with a Cumulative Grade Point Average of 85.6 %

Pre-University Course (Intermediate)

2018 - 2020

Rajiv Gandhi University Of Knowlodge And Technologies, Srikakulam, AP

Completed my 12th in PCM with a percentage of 87.8 %

High School

2018

Z.P.P.HIGH SCHOOL, Konaseema, AP, India

Completed my 10th with a percentage of 100 %


Languages and Technologies

Programming Languages

C , Python , JavaScript , PHP

Familiar

TensorFlow , Data Analysis ,NLP fundamentals , Object-oriented programming ,SQL , Deployment Architecture, Open AI ,Hugging Face

Web Design

HTML5, CSS3, SCSS, JavaScript,React JS

Database

MySQL, MongoDB

Version Control

Git

Machine Learning and Data Science

Power BI,Machine Learning Libarires,Numpy, Pandas, Matplotlib, Tensorflow,CNN


Research

Bioremidation Of Surgical Masks Using Microbes:

Contact

Feel free to reach out to me.

Location:

Amalapuram, Konaseema District, Andhra Pradesh, India

* indicates mandatory field

Loading
Your message has been sent. Thank you!