Hi, I'm Deepak NR.
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Computer Vision | Deep Learning | Crafting AI Solutions from Scratch | Immediate Joiner | I help Companies Optimize Data-Driven Strategies
About
Hello, I'm Deepak NR, skilled in Computer Vision, Deep Learning, and Data Science in Python. I'm passionate about AI and hold a track record of streamlining projects, such as Automatic License Plate Recognition and Face Recognition, improving model efficiency by 20%. I'm dedicated to leveraging my skills in Object Detection, Object Tracking, and Optical Character Recognition to drive innovation. Currently, I'm eager to collaborate on impactful AI projects. Let's explore possibilities together!
- Languages: Python, Julia, C++, HTML/CSS
- Databases: MySQL, MongoDB
- Libraries: NumPy, Pandas, OpenCV, Scikit
- Frameworks: Computer Vision, Deep Learning, Machine Learning, Flask, FastAPI, Keras, TensorFlow, PyTorch, PySpark, RabbitMQ
- Tools & Technologies: Git, Docker, Data Annotation, Ubuntu, Optical Character Recognition
Looking for an opportunity to work in a challenging position combining my skills in Software Engineering, which provides professional development, interesting experiences and personal growth.
Experience
- Collaborated on the installation of WebODM using Docker, as well as data integration and service management.
- Employed image processing methods to improve drone imagery. Tools: Python, Image Processing, Docker
- Designed a self-annotation system for annotating object detection data (Raw data).
- Provided technical support to clients and collaborated with cross-functional teams to resolve technical issues.
- Actively participate and contribute to the internal data science project initiatives.
- Tools: Python, FLask
- Streamlined two major projects, namely Automatic License Plate Recognition and Face Recognition and improved the inference time of the models by 20%.
- Designed and custom-trained Object detection (YOLOv4)/OCR frameworks (Tesseract OCR/CRNN).
- Built a modular video analytics app using Flask, OpenCV that tracks the location of each human in a multi-camera environment; utilised perspective transformation, object detection, and object tracking to find the location of a human.
- Assembled about 100k+ of data for training various deep-learning models.
- Annotating raw data for custom Object detection training using Computer Vision Annotation Tool (CVAT) .
- Having good interactions with IDEs like Google Colab, Jupiter Lab, PyCharm, and VS Code.
- Collaborated with product development and engineering teams to identify and prioritise critical technical issues; contributed to the successful resolution of 50+ bugs.
- Tools: Python, Flask, OpenCV, Keras, Tensorflow, PyTorch
Projects
A Python-based video captioning tool.
A Guide to Custom Training YOLOv8 for Safety Helmet Detection.
- Tools: Python, YoloV8, Object Detection, Computer Vision, Deep Learning
- This project is a detailed resource for implementing YOLOv8, a state-of-the-art object detection model, tailored specifically for safety helmet detection in diverse environments.
- Whether you're a beginner or an experienced developer, this guide walks you through the entire process, from dataset preparation to model training and deployment.
Pothole-and-Plain-road-images-classification using Convolutional Neural Network.
A simple example of using Fast API and Googletrans in Python.
Skills
Languages and Databases
Python
Julia
HTML5
MySQL
MongoDB
Shell Scripting
Libraries
NumPy
Pandas
OpenCV
scikit-learn
matplotlib
Frameworks
FastAPI
Flask
Keras
TensorFlow
PyTorch
Education
Adichunchanagiri Institute of Technology
Chikkamagaluru, India
Degree: Bachelor of Engineering in Computer Science and Engineering
CGPA: 7.45
- Volunteered for the 1st International Conference on Advances in Information Technology (ICAIT-2019).
- Computer Vision Internship project: Recognizing Different Species of Monkey