yudhv Goto Github PK

advanced-lane-finding

Using various Computer Vision techniques like Perspective Transforms, Camera Calibration, Sobel Operations, I use a robust method of finding lane lines on the road.

alexnet-feature-extraction

Part of Udacity's Self Driving Nanodegree where I learn how to use feature extraction for Transfer Learning

automated-question-answering

Natural Language Processing based project that uses Wikipedia, NLTK, and NumPy to answer factoid questions.

behavioral-cloning

I make a model learn purely from past driving data and make a car drive autonomously in a simulator. Pretty cool!!

burgerbuilder

[WORK IN PROGRESS] A React App that allows one to build their own custom burger

datastructure

A set of common data structures implemented in Java

dicejs

A simple front-end game of dice

extended-kalman-filter

Uses the Extended Kalman Filter algorithm to predict the movement of objects in the environment. Uses Lidar and Radar data as input.

front-end-interview-handbook

🕸 Almost complete answers to "Front-end Job Interview Questions" which you can use to interview potential candidates, test yourself or completely ignore

heat

instaclone

An instagram clone in react native

javascript-basic-projects

kickstart.nvim

A launch point for your personal nvim configuration

patchwork

All the Git-it Workshop completers!

profilesite

Personal Website

pytrading

A Python based High Frequency Trading system that uses the Kite Connect API

readme-best-practices

Best practices for writing a README for your open source project

recipefetcher

A website that serves recipes (3rd party APIs), shopping lists, and a simple saving feature.

restjava

Project done as a part of the MSCDA program at SMU, Halifax, Canada. A Java server is built from scratch to handle RESTful calls of GET, POST, PUT, and DELETE.

seo

An aggregation of all the lessons I learn during my SEO journey

starter

Starter template for LazyVim

sttm-web

STTM website - https://www.sikhitothemax.org

traffic-sign-classifier

A CNN model that has 97.5% testing accuracy on the GTSRB (German Traffic Signs) dataset.

transfer-learning-lab

As part of Udacity's Self Driving Car Nanodegree, we used transfer learning to employ ImageNet trained neural networks like GoogLeNet, ResNet, VGG on Traffic Signs and Cifar10 datasets

vehicle-detection

Tracks vehicles on the road through this project. Uses HOG features in conjunction with a Support Vector Classifier to identify cars.