VirkSaab/Standard-Neural-Network-with-MNIST-data

Stars
2
Language
Jupyter Notebook
Created over 6 years ago
Updated over 6 years ago

VirkSaab/Standard-Neural-Network-with-MNIST-data

VirkSaab

There are no reviews yet. Be the first to send feedback to the community and the maintainers!

Car-Parking-Alarm-System

Security alarm system using Arduino Uno R3 microcontroller, Ultrasound sensor HC-SR04 and Arduino IDE 1.6.8. Applications of this system ranges from security systems like automated-safe security systems to car parking systems, Work on a simple system where the distance of object is measured from the ultrasound sensors and if any object is in the hazardous range then the buzzer goes on. The intensity of sound keeps on increasing as the obstacle approaches near to the ultrasonic sensors. This feature makes them an appropriate system to be embedded in cars and automobiles for parking measures as it will help determine the distance from obstacles.

Home-Automation

Home automation system built on Arduino Uno R3 microcontroller along with Light sensor, Motion detector, Temperature sensor, Gas sensor, Sound sensor, Buzzer, LED lights, Crystal Display and Arduino IDE 1.6.8. Home automation is the residential extension of building automation and involves the control and automation of lighting, temperature sensing, appliances, and security. The System is controlled by Arduino microcontroller which is connected to a computer for power as well as for monitoring the outputs of different sensors using serial monitor on Arduino IDE. Security sensors such as motion detector and gas sensor interact with buzzer and LED for alerts. Display unit provides the information of temperature and special messages.

TensorFlow-data-pipeline

Jupyter Notebook

Best-Flat-theme-for-Jupyter-Notebook

This custom theme is really beautiful and modern looking. It is based on flat design. Give it a try!

ai_uninformed_search_algorithms_interactive_webapp

Virksaab.github.io

Jupyter Notebook

YAMLF

Yet Another Machine Learning Framework (YAMLF) is a lite machine learning and deep learning models training and inference framework. It contains data augmentations, data loaders, training routines that we usally rewrite for every ML project.

Web_Crawler

This code will build a web crawler which will collect links from html pages

Lane-detection-in-GTA-5-Video-Game

Teacher-Review-System

auto_photomontage_webapp

Applied-Data-Science-with-Python

A Specialization offered by University of Michigan at coursera.com

Jupyter Notebook

Twitter-Sentiment-Analysis

BODMAS

BODMAS stands for Brackets, Orders or pOwers, Division, Multiplication, Addition, and Subtraction. I used Python 3.5 for this project. It will randomly generate an Elementary mathematics question based on BODMAS and ask the user to answer it. If user gives correct answer then corresponding points will be added to user's score which will be saved in a text file when you end a particular session. If user gives incorrect response then it tells the user that answer is wrong and shows correct answer to user for that question. It ask for user name at start so that it can store scores with user's names which also gives flexibility to store multiple users score.