arvindkrvartiya Goto Github PK

adminlte

AdminLTE - Free admin dashboard template based on Bootstrap 4

autonomous-delivery-robot

Repository for Autonomous Delivery Robot project of IvLabs, VNIT

autopilot

A simple self-driving car module for humans 🚘 🛣️

coursera-html-css-and-javascript-for-web-developers

This repository holds the assignments of the Course : HTML, CSS, and Javascript for Web Developers by Johns Hopkins University

django-e-commerce

django-ecommerce

Ecommerce website built with Django 2.2.3, Python 3.7.3, Stripe and AWS

django-ecommerce-1

This is a E-Commerce Website

django-ecommerce-2

Django-ecommerce is a fully open-source E-commerce platform built using Django Web Framework, designed with Bootstrap4...

django-subscription

Subscriptions or Recurring Billing App for django

e-learning-django-

e-learning-platform

a fully functional Django e-learning platform

e-learning-platform-1

This is an E-learning platform built on top of Django.

e-learning-website

E-Learning Website using Django

edx-platform

The Open edX platform, the software that powers edX!

elearning

e-learning django app (django, python)

elearning-1

an e-learning website with recommender system,

elearning-website-with-django-and-python

A project on eLearning Site using Django and SQLite.

faster-rcnn.pytorch

A faster pytorch implementation of faster r-cnn

fullstack-course4

Example code for HTML, CSS, and Javascript for Web Developers Coursera Course

gans-tensorflow2

🚀 Variants of GANs most easily implemented as TensorFlow2. GAN, DCGAN, LSGAN, WGAN, WGAN-GP, DRAGAN, ETC...

gans.tensorflow.v2

gdl_code

The official code repository for examples in the O'Reilly book 'Generative Deep Learning'

human-activity-recognition-with-neural-network-using-gyroscopic-and-accelerometer-variables

The VALIDATION ACCURACY is BEST on KAGGLE. Artificial Neural Network with a validation accuracy of 97.98 % and a precision of 95% was achieved from the data to learn (as a cellphone attached on the waist) to recognise the type of activity that the user is doing. The dataset's description goes like this: The sensor signals (accelerometer and gyroscope) were pre-processed by applying noise filters and then sampled in fixed-width sliding windows of 2.56 sec and 50% overlap (128 readings/window). The sensor acceleration signal, which has gravitational and body motion components, was separated using a Butterworth low-pass filter into body acceleration and gravity. The gravitational force is assumed to have only low frequency components, therefore a filter with 0.3 Hz cutoff frequency was used.

intro-to-self-driving-cars

Intro to Self Driving Cars Nano Degree Udacity

intro-to-self-driving-cars-1

Self driving cars of udacity

keras-gan

Keras implementations of Generative Adversarial Networks.

keypoint_communities

[ICCV '21] In this repository you find the code to our paper "Keypoint Communities".

kidney-disease-classification-deep-learning-project

led_cube

8x8x8 LED cube powered by an arduino

mit_python_assignment