nkrgit,Naga Kiran Reddy,github

Hola👋, I'm Kiran👨‍💻

🌱 I’m currently learning AI/VR/AR
📫 How to reach me: [email protected]
⚡ What's on my mind: VR/AR/Holograms
I am well versed with Python, C, Java, along with technology modules like :
Numpy, Pandas, Seaborn, Matplotlib, Sklearn, OpenCV, NLTK, GeoPandas, Gym (i.e. Open AI RL) and Deep Learning frameworks: Tensorflow and Keras
Certifications
-> AWS Elements of Data Science
-> Data Analytics from Kaggle
-> Deep Learning Specialization
-> Machine Learning Specialization
-> Computer Vision
-> Sequence models (i.e., Natural Language Processing)
Hardware modules
1. Arduino (Arduino IDE),
2. Raspberry pi3 (Raspbian Stretch) etc

My work on Kaggle!!

1. Amazon book recommendations,
2. Netflix Recommendations,
3. Reinforcement Learning: SARSA on Grid world Env,
4. Reinforcement Learning Algorithms: Key features, pros and cons,
5. Data Cleaning & Neural Network Optimization

Below is my work I'm proud of!!

Naga Kiran Reddy's Projects

android-app-for-text-recognition

Designed and developed an android app that can recognize and detect text from images using Vision API.

computer-vision-and-image-processing

Created a panorama image (i.e., by stitching) from two separate images and developed filters to detect edges along different directions in an image. Performed morphological operations to denoise and extract boundaries from noisy images

deep-learning-work

Repo includes exercises done related to Deep Neural Networks, Computer Vision and Natural Language Processing Applications

fleet-scheduling-using-maddpg-multi-agent-rl

Developed a Multi-Agent DDPG to solve Vehicle Scheduling problem.

home-surveillance-system-using-computer-vision

Built a Home Surveillance system using Computer Vision: Deep Convolution Neural Networks.

nkrgit

Kiran Git Profile

object-detection-on-raspberry-pi3

Developed an object detection model trained on the COCO dataset, which can detect 90 different objects. Deployed the TensorFlow Lite version of the same model on Raspberry pi3.

object_recognition-on-drone

The goal of this project is to identify objects of interest in a scene, where an object detection is ran on a live video data transmitted wirelessly from drone to ground station using an HDMI transmitter/receiver configuration.