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Alluru Sai shree ganeshAG
Open to opportunities

Alluru Sai shree ganesh

@allurusaishreeganesh

Aspiring data scientist building machine learning and computer vision systems with Python, deep learning, and clean code.

India
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What I'm looking for

I’m looking for an entry-level role where I can apply data science and machine learning to real-world problems—especially computer vision and alerting systems—while continuing to grow engineering fundamentals and model-building skills.

I’m an aspiring data scientist focused on building practical machine learning and computer vision solutions. I’ve trained with Python and core ML libraries like NumPy, Pandas, Matplotlib, TensorFlow, and Scikit-Learn, and I enjoy turning real-world signals into reliable predictions.

Along the way, I strengthened my engineering foundation through a C++ summer internship where I worked on object-oriented programming, data structures and algorithms, and debugging projects involving file handling, memory management, and multithreading. My projects include a real-time animal detection system using a deep-learning object detection model (YOLO) with alert logic for collision prevention, and an ML-based sleep apnea monitoring system that processes airflow and oxygen signals to classify apnea events with real-time alerts.

Experience

Work history, roles, and key accomplishments

Education

Degrees, certifications, and relevant coursework

SC

Sashara Junior College

Intermediate, Intermediate

2020 - 2022

Grade: 88%

Completed the Intermediate program at Sashara Junior College with a percentage of 88% from 2020 to 2022.

Lovely Professional University logoLU

Lovely Professional University

Bachelor of Technology, Computer Science Engineering

Grade: CGPA: 5.5

Completed a Bachelor of Technology in Computer Science Engineering at Lovely Professional University, graduating in 2022 with a CGPA of 5.5.

PS

Pragati High School

Matriculation, Matriculation

2019 - 2020

Grade: 87%

Completed Matriculation at Pragati High School with a percentage of 87% from 2019 to 2020.

Tech stack

Software and tools used professionally

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