I'm K. Jyothi Sai Raju, currently pursuing my Bachelor of Technology (B.Tech) degree in Computer Science and Engineering at N.B.K.R ist college. I have a strong passion for technology and programming. Throughout my academic journey, I have gained valuable knowledge and skills in various programming languages, web development.In addition to web development, I have developed a keen interest in machine learning. I have been learning and experimenting with machine learning algorithms, data preprocessing, and model training. I believe machine learning holds immense potential in solving real-world problems and I'm excited to contribute to this field.
Skills
Certificates
Internships
Bachelor of Technology-Computer Science and Engineering
CGPA:
7.5 (TILL DATE)
Diploma in electronic communication and engineering
Percentage:
80.53
10th CBSE
CGPA: 7.0
This website serves as a comprehensive weather reporting system, providing accurate and up-to-date information on temperature, humidity, maximum and minimum wind speed, weather forecasts, and the ability to access weather reports for any desired location
Technology
This Website hosts a machine learning project employing a decision tree classifier to predict loan eligibility based on diverse applicant features. It includes a user-friendly web application for individuals to input their details and receive predictions regarding their loan approval status.
Technology
Zenith Virtual Assistant is a groundbreaking project that brings the power of voice control to enhance productivity and efficiency like never before. Imagine having a personal assistant at your beck and call, ready to execute tasks with just the sound of your voice.
Technology
Experience the Wireless Sound Control System using Camera, a cutting-edge solution for hands-free volume control of your computer's audio. Utilizing advanced hand gesture recognition, effortlessly adjust volume levels with precision and ease.
Technology
This website features a Python web app tailored to forecast Air Quality Index (AQI) via input parameters. The app harnesses a random forest model from scikit-learn, trained on the Air Quality Data Set, ensuring accurate predictions.
Technology
Phishing URL Detection project utilizes Gradient Boosting Classifiers to accurately identify phishing websites, enhancing online security by distinguishing between legitimate and malicious URLs with high precision and resilience.
Technology