narrasriram

Albert-Sentiment-Analysis

Google's Natural Language Processing model with SOT result in various tasks

backend-challenge-go

Behavioural-Cloning-of-Self-Driving-Car

Towards a trend in bridging the gap of building the Self-Driving vehicles using Convolutional Neural Networks, cloning the behavior of a trained vehicle data onto another platform could be a challenging task to deal with random obstacles like biased nature in data. The most general case could be observed when training the vehicle on a one way circular track and transfer that knowledge to a vehicle on different track. In this project, NVidia model of Convolutional Neural Networks is used to train the car with required Data Augmentation techniques to reduce the influence of biased data in detecting the steering angle of the Vehicle. The initial training to the car in a circular track of simulator has been given in clockwise, anticlockwise directions. The error prone zones are analyzed and provided more information with different image manipulation techniques. Transferred knowledge of the generalized trained data has been tested on a different track in the simulator with required augmentation techniques induced.

Breast-Cancer-Detection

Cardiovascular_Disease_Detection

Computer-Audio---Radix-2-Cooley-Tukey-FFT

Covid-19_Detection_and_Interpretation_in_Chest_X-Ray_Images

data_science

DonorsChoose_Visualization

Source for blog post: Interactive Data Visualization with D3.js, DC.js, Python, and MongoDB

EMOTION-RECOGNITION-USING-FINE-TUNED-MODELS-ERFM-

narrasriram/Albert-Sentiment-Analysis

Google's Natural Language Processing model with SOT result in various tasks

narrasriram/backend-challenge-go

narrasriram/Behavioural-Cloning-of-Self-Driving-Car

Towards a trend in bridging the gap of building the Self-Driving vehicles using Convolutional Neural Networks, cloning the behavior of a trained vehicle data onto another platform could be a challenging task to deal with random obstacles like biased nature in data. The most general case could be observed when training the vehicle on a one way circular track and transfer that knowledge to a vehicle on different track. In this project, NVidia model of Convolutional Neural Networks is used to train the car with required Data Augmentation techniques to reduce the influence of biased data in detecting the steering angle of the Vehicle. The initial training to the car in a circular track of simulator has been given in clockwise, anticlockwise directions. The error prone zones are analyzed and provided more information with different image manipulation techniques. Transferred knowledge of the generalized trained data has been tested on a different track in the simulator with required augmentation techniques induced.

narrasriram/Breast-Cancer-Detection

narrasriram/Cardiovascular_Disease_Detection

narrasriram/Computer-Audio---Radix-2-Cooley-Tukey-FFT

narrasriram/Covid-19_Detection_and_Interpretation_in_Chest_X-Ray_Images

narrasriram/data_science

narrasriram/DonorsChoose_Visualization

Source for blog post: Interactive Data Visualization with D3.js, DC.js, Python, and MongoDB

narrasriram/EMOTION-RECOGNITION-USING-FINE-TUNED-MODELS-ERFM-

narrasriram/Flanging-Effect

narrasriram/frontend-basics

HTML, CSS and Java Script Development Basics

narrasriram/Generation_and_Analysis_of_Flanging_and_Chorous_Effects

narrasriram/Git-Commands

A list of commonly used Git commands

narrasriram/InfoVizProject

narrasriram/machine-learning-nd

Udacity's Machine Learning Nanodegree project files and notes.

narrasriram/Programming

narrasriram/Prostate-Cancer-Detection

narrasriram/self-driving-car-nd

Udacity's Self-Driving Car Nanodegree project files and notes.

narrasriram/Slack