vivek kiran User

Engineered a U-Net deep learning model for precise segmentation of grape bunches in high-resolution vineyard images, enhancing vineyard management with pixel-level accuracy. Optimized training with TensorFlow using Binary Cross-Entropy loss, Adam optimizer, and essential callbacks, achieving high precision and recall.

Engineered a U-Net deep learning model for precise segmentation of grape bunches in high-resolution vineyard images, enhancing vineyard management with pixel-level accuracy. Optimized training with TensorFlow using Binary Cross-Entropy loss, Adam optimizer, and essential callbacks, achieving 86% Precision, 81% Recall, and 71% Mean IoU.

Developed a highly functional humanoid robot, integrating ChatGPT to enhance its conversational and interactive capabilities with humans. Utilized Python and libraries like pyfirmata, pyaudio, pyttsx3, OpenAI, and SpeechRecognition to enable seamless communication between the robot and users.

Developed a highly functional humanoid robot leveraging cutting-edge technologies, including the integration of ChatGPT, to enhance its conversational abilities and interactive capabilities with humans. Utilized Python programming language and inbuilt libraries such as pyfirmata, pyaudio, pyttsx3, openAi, and SpeechRecognition to enable seamless communication between the humanoid robot and users.

Developed a machine learning model for human activity detection using cell phone sensor data, leveraging Python libraries like Pandas, NumPy, Scikit-learn, and TensorFlow. Implemented a Flask web application for data processing and visualization, training and evaluating classification algorithms such as SVM and Random Forests.

Developed a machine learning model for human activity detection using cell phone sensor data, leveraging Python libraries such as Pandas, NumPy, Scikit-learn, and TensorFlow. Implemented a Flask web application for data processing, model prediction, and visualization, training and evaluating SVM and Random Forests for activity classification.

Developed an interactive news research application in Python using Streamlit, allowing users to input URLs and questions to retrieve insights from articles. Engineered a system that processes articles, vectorizes text using OpenAI embeddings, and indexes with FAISS for fast similarity search, providing AI-powered answers via ChatGPT.

Developed an interactive news research application in Python using Streamlit, enabling users to retrieve insights from articles by inputting URLs and questions. Engineered a system that processes articles, vectorizes text using OpenAI embeddings, and indexes using FAISS for fast similarity search, providing answers from processed articles using ChatGPT.

Grade: 7.93 on a scale of 10

Pursuing a Bachelor of Technology in Electrical Engineering, focusing on fundamental principles and advanced applications. Coursework includes linear algebra, data structures and algorithms, and basic machine learning. Maintaining a strong academic record with a CGPA of 7.93.

Grade: 96.4%

Completed pre-university studies, focusing on science subjects under the Telangana State Board. Achieved a strong academic record, demonstrating proficiency in core curriculum.

Grade: 96.4%

Completed intermediate education under the Telangana State Board, achieving a percentage of 96.4. Focused on a comprehensive curriculum to build a strong academic foundation for higher studies.