AbdullahMoustafa

AbdullahMoustafa.github.io

ADCTIVACDRIVER

ADC driver for Tiva-C controller based on ARM processor

AdvancedLaneDetection

Self-Driving Car Nano-degree Project

AI-Virtual-Assistant

AI virtual assistant using python GUI interface, GENIA virtual assistant features: 1-Web Scrapping HTML pages . Wikipedia . Weather State . Covid19 Statistics 2-Simple Calculator 3-Talktive Assistant 4-Sending Emails 5-Date/Time 6-Open websites 7-Play music 8-Access programs 9-Search on google 10-Simple GUI 11-Games(snake) 12-Draw and Save 13-Chating output box 14-Translate from English to four foreign languages . French . Spanish . German . Italian . Portuguese

chatbot-with-python

AI Chatbot GUI using Tensorflow

Company-Calendar

Company calendar using java where user enter the month, year, and company name to generate a calendar of the month.

CoverLetterCreator

Cover letter creator GUI using python [ Tkinter - Reportlab ]

Data-Science-Specializtion-IBM

Data Science Specialization Capstone project by IBM and Coursera

DataAnalysis-Udicity

1 Million Arab coder - Data Analysis Track (Solutions)

SimpleLaneDetection

In this project, you will be writing code to identify lane lines on the road, first in an image, and later in a video stream (really just a series of images). To complete this project, we used the tools we learned about in Udacity self-driving cars nanodegree, and build upon them. Our first goal is to write code including a series of steps (pipeline) that identify and draw the lane lines on a few test images. We successfully identify the lines in an image, then we wrote a code into the block provided to run on a video stream. The algorithm we used to detect the lanes divided into functions that will be running on the test video “test2.mp4” there is five functions used which are canny, region_of_interest, make_coordinates, average_slope_intercept, and display_lines. Python programming was our language to write the code and we used some popular modules as OpenCV, NumPy, and matplotlib. Finally, this report will discuss all those functions and how we implement mathematics, programming and computer vision to our real-life use to be a part of our final project “Self-driving car”.

AbdullahMoustafa/AI-Virtual-Assistant

AI virtual assistant using python GUI interface, GENIA virtual assistant features: 1-Web Scrapping HTML pages . Wikipedia . Weather State . Covid19 Statistics 2-Simple Calculator 3-Talktive Assistant 4-Sending Emails 5-Date/Time 6-Open websites 7-Play music 8-Access programs 9-Search on google 10-Simple GUI 11-Games(snake) 12-Draw and Save 13-Chating output box 14-Translate from English to four foreign languages . French . Spanish . German . Italian . Portuguese

AbdullahMoustafa/SimpleLaneDetection

In this project, you will be writing code to identify lane lines on the road, first in an image, and later in a video stream (really just a series of images). To complete this project, we used the tools we learned about in Udacity self-driving cars nanodegree, and build upon them. Our first goal is to write code including a series of steps (pipeline) that identify and draw the lane lines on a few test images. We successfully identify the lines in an image, then we wrote a code into the block provided to run on a video stream. The algorithm we used to detect the lanes divided into functions that will be running on the test video “test2.mp4” there is five functions used which are canny, region_of_interest, make_coordinates, average_slope_intercept, and display_lines. Python programming was our language to write the code and we used some popular modules as OpenCV, NumPy, and matplotlib. Finally, this report will discuss all those functions and how we implement mathematics, programming and computer vision to our real-life use to be a part of our final project “Self-driving car”.

AbdullahMoustafa/AbdullahMoustafa.github.io

AbdullahMoustafa/ADCTIVACDRIVER

ADC driver for Tiva-C controller based on ARM processor

AbdullahMoustafa/AdvancedLaneDetection

Self-Driving Car Nano-degree Project

AbdullahMoustafa/chatbot-with-python

AI Chatbot GUI using Tensorflow

AbdullahMoustafa/Company-Calendar

Company calendar using java where user enter the month, year, and company name to generate a calendar of the month.

AbdullahMoustafa/CoverLetterCreator

Cover letter creator GUI using python [ Tkinter - Reportlab ]

AbdullahMoustafa/Data-Science-Specializtion-IBM

Data Science Specialization Capstone project by IBM and Coursera

AbdullahMoustafa/DataAnalysis-Udicity

1 Million Arab coder - Data Analysis Track (Solutions)

AbdullahMoustafa/DistributionsPythonPackage

Python package of Gaussian Distribution and Binomial Distribution, and files ready to uploaded to PyPi

AbdullahMoustafa/DXwand-Task

Retrieval arabic chatbot TFIDF & LSTM with text classifier

AbdullahMoustafa/EcontactApp

Econtact Application using C# and .Net framework implementing OOP concept.

AbdullahMoustafa/GPIOTIVACdriver

GPIO driver for Tiva-C-Series-TM4C123G-LaunchPad

AbdullahMoustafa/Machine-Learning-Models

face identification & recognition, speech recognition , and Text Multi Classifier

AbdullahMoustafa/newproject

AbdullahMoustafa/ObjectAvoidanceCar

Object Avoiding Car using ARM controller

AbdullahMoustafa/Projask_AndriodApp1

AbdullahMoustafa/repogithub

AbdullahMoustafa/Sanke-Game

Snake game

AbdullahMoustafa/SSHremoterepo

AbdullahMoustafa/SW_LayeredAutosar

AUTOSAR project (PORT/DIO drivers)

AbdullahMoustafa/Tensorflow-In-Practice-Specialization

Tensorflow In Practice Specialization weekly projects by deeplearning.ai and Coursera

AbdullahMoustafa/Tensorflow-syllabus

Notebooks for learning deep learning

AbdullahMoustafa/Timer0driverTivaC

Timer0 driver for Tiva-C microcontroller based on ARM processor

AbdullahMoustafa/Tiva-C-Series-TM4C123G-LaunchPad-HC06-Bluetooth-Module

AbdullahMoustafa/TkinterGUIs

TkinterGUIs - My python GUI course projects.

AbdullahMoustafa/UltrasonicSensorTivaC

Interfacing of Ultrasonic sensor with TIVA-C ARM Cortex

AbdullahMoustafa/YOLOobjectdetectionOpenCV

YOLO algorithm that can detect 80 different object using openCV and transfer learning of trained model weights and opencv library to provide the real time video playing with important info as rectangle around the detected object with the name of the label also the accuracy of it if greater then 50 % confidence.