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atharvamusale Goto Github PK

followers: 16.0 following: 15.0 repos: 13.0 gists: 16.0

Type: User

Company: Quantiphi

Bio: Machine Learning/ Deep Learning Enthusiast

Twitter: AtharvaMusale

Location: Mumbai,India

Blog: [email protected]

About Me

I'm Atharva Musale, a driven Master's student in Computer Science at SUNY Buffalo, specializing in Artificial Intelligence. My professional background includes a pivotal role as a Machine Learning Engineer at Quantiphi Analytics Solutions, where I developed sophisticated AI models and engineered robust software solutions. My expertise spans machine learning, deep learning, computer vision, data engineering, and software development, supported by comprehensive academic coursework and practical experience. I have successfully designed and implemented projects such as theme park safety systems using advanced object detection techniques, automated claim adjudication systems, and efficient data pipelines, significantly enhancing operational efficiencies and accuracy in real-world applications.

Reach out to me at [email protected] or connect on LinkedIn.

atharvamusale's Projects

atharvamusale

atharvamusale.github.io

diabetic_retinopathy

Deep Learning and Neural Networks are used to predict the severity of impending blindness

donorschoose-application-acceptance

language-translation-using-attention-mechanism

machine-learning-collection

A resource for learning about ML, DL, PyTorch and TensorFlow. Feedback always appreciated :)

machinelearningnotebooks

Python notebooks with ML and deep learning examples with Azure Machine Learning | Microsoft

ml-basics-exploration

neetcode

LeetCode Repo

python_algorithms

All Algorithms implemented in Python

reducing-commercial-aviation-fatalities

semantic-segmentation-on-indian-driving-dataset

vehicle-detection-and-tracking-using-yolov3-and-deep-sort

I have used YOLOv3 Algorithm for Vehicle Detection and Deep Sort Algorithm for Vehicle Tracking. After tracking the vehicles I have tried counting the number of vehicles in each lane. This will help us in real life implementations like Toll Booths(To cross check the collection) and Traffic Lanes Rules Monitoring(To check if heavy vehicles are following the proper lanes or not).

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