About Ahmed Gad

Ahmed Gad received his B.Sc. degree with excellent with honors in information technology from the Faculty of Computers and Information (FCI), Menoufia University, Egypt, in July 2015. For being ranked first in his faculty, he was recommended to work as a teaching assistant in one of the Egyptian institutes in 2015 and then in 2016 to work as a teaching assistant and a researcher in his faculty. His current research interests include deep learning, machine learning, artificial intelligence, digital signal processing, and computer vision.

Ahmed Gad Posts (17)

• Artificial Neural Networks Optimization using Genetic Algorithm with Python - 18 Mar 2019
  
  This tutorial explains the usage of the genetic algorithm for optimizing the network weights of an Artificial Neural Network for improved performance.
• Artificial Neural Network Implementation using NumPy and Image Classification - 21 Feb 2019
  
  This tutorial builds artificial neural network in Python using NumPy from scratch in order to do an image classification application for the Fruits360 dataset
• Building Surveillance System Using USB Camera and Wireless-Connected Raspberry Pi - 06 Nov 2018
  
  Read this post to learn how to build a surveillance system using a USB camera plugged into Raspberry Pi (RPi) which is connected a PC using its wireless interface.
• Building an Image Classifier Running on Raspberry Pi - 09 Oct 2018
  
  The tutorial starts by building the Physical network connecting Raspberry Pi to the PC via a router. After preparing their IPv4 addresses, SSH session is created for remotely accessing of the Raspberry Pi. After uploading the classification project using FTP, clients can access it using web browsers for classifying images.
• Intuitive Ensemble Learning Guide with Gradient Boosting - 30 Jul 2018
  
  This tutorial discusses the importance of ensemble learning with gradient boosting as a study case.
• Genetic Algorithm Implementation in Python - 24 Jul 2018
  
  This tutorial will implement the genetic algorithm optimization technique in Python based on a simple example in which we are trying to maximize the output of an equation.
• Beginners Ask “How Many Hidden Layers/Neurons to Use in Artificial Neural Networks?” - 16 Jul 2018
  
  By the end of this article, you could at least get the idea of how these questions are answered and be able to test yourself based on simple examples.
• Packaging and Distributing Your Python Project to PyPI for Installation Using pip - 11 Jun 2018
  
  This tutorial will explain the steps required to package your Python projects, distribute them in distribution formats using steptools, upload them into the Python Package Index (PyPI) repository using twine, and finally installation using Python installers such as pip and conda.
• Complete Guide to Build ConvNet HTTP-Based Application using TensorFlow and Flask RESTful Python API - 15 May 2018
  
  In this tutorial, a CNN is to be built, and trained and tested against the CIFAR10 dataset. To make the model remotely accessible, a Flask Web application is created using Python to receive an uploaded image and return its classification label using HTTP.
• Building Convolutional Neural Network using NumPy from Scratch - 26 Apr 2018
  
  In this article, CNN is created using only NumPy library. Just three layers are created which are convolution (conv for short), ReLU, and max pooling.