SAI VAMSI M

AIML Engineering Student | Aspiring AI/ML Engineer

Bengaluru, IN.

About

Highly motivated AIML Engineering student with hands-on experience in developing and deploying AI/ML solutions, specializing in deep learning techniques. Proven ability to translate complex data science principles into practical applications, demonstrated through impactful projects in predictive modeling and intelligent systems. Eager to leverage strong analytical and programming skills to drive innovation and solve real-world challenges in artificial intelligence and machine learning.

Education

New Horizon College Of Engineering

Bengaluru, Karnataka, India
→
Bachelor of Engineering Artificial Intelligence and Machine Learning Grade: CGPA of 7.42 (currently pursuing 6th semester)

Narayana Junior College

Andhra Pradesh, Andhra Pradesh, India
→
Intermediate Education Pre-University Course Grade: 55.10%

CVR Memorial High School

Andhra Pradesh, Andhra Pradesh, India
→
Secondary Education High School Education Grade: 98%

Certificates

Gen AI Courses

IBM

Introduction to Natural Language Processing

Great Learning

Skills

Programming Languages

Python, SQL, Java.

Machine Learning

Deep Learning, Predictive Modeling, Data Science, Statistical Analysis.

Soft Skills

Adaptability, Leadership, Collaboration.

Natural Language Processing

NLP, Voice Command Systems.

Software Development

Clean Code, Efficient Code, Functional Software Solutions.

Projects

NLP Voice Command System for Drivers

→

Summary

Developed an intuitive voice-controlled interface for vehicle functions, aiming to enhance driver safety and reduce manual controls.

Heart Disease Prediction Using Machine Learning With Python

→

Summary

Engineered a machine learning model to predict heart disease risk using various patient health indicators, applying data science and statistical methodologies.

Wine Quality Prediction Using Machine Learning With Python

→

Summary

Developed a machine learning model to predict wine quality based on various input factors, integrating principles from data science, statistics, and viticulture.