Name: Omar Mohamed
Type: User
Company: Faculty of Engineering , Alexandria University.
Bio: I am Omar Mohamed an electrical engineering graduate. I am passionate about Machine and Deep learning and eager to apply them in real world problems.
Location: Alexandria, Egypt
Blog: https://www.linkedin.com/in/omar-mohamed-mounir-b81ab2187/
Omar Mohamed's Projects
If you are going to take this course ; you will be able to create convolutional neural network image classification and segmentation models to make diagnoses of lung and brain disorders.
This code has succeded in flying a simple drone project
This is the complementary code repository for the BINet papers.
This repository contains all "CNN Tensorflow" coursera course assignments to help others who didn't finish the course and struggle with their assignment to finish the course
CoroNet is a Covid-19 detection and diagnosis tool. It scans chest x-rays and clasifies it into normal, pneumonia or covid classes
A data pre-processing code for those who aren't familiar with machine learning and deep learning , it can helps you know how to handle csv data , read it and fill its missings. And here I also added some code for predictions that can help you as well
When it comes to creating a Machine Learning pipeline, data preprocessing is the first step marking the initiation of the process. Typically, real-world data is incomplete, inconsistent, inaccurate (contains errors or outliers), and often lacks specific attribute values/trends. This is where data preprocessing enters the scenario β it helps to clean, format, and organize the raw data, thereby making it ready-to-go for Machine Learning models. Letβs explore various steps of data preprocessing in machine learning, but firstly we need to understand the concept of Noisy data.
Data on number of births every month for approx 135 counties. The columns are self-explanatory, I have described the important columns below. Country or area: The name of the country. Year: the year for which the record is stored. Month: The name of the month. Number of births: The total number of births that happed in the month. Code tries to understand and interpret data in Sweden and you can generalize by trying other areas.
In this tutorial we will: Chat with a neural network model! Show how to use common commands in ParlAI, like inspecting data and model outputs. See where to find information about many options. Show how to fine-tune a pretrained model on a specific task. And other things as well you can do with the large scale project ParlAI that aim to change the perception of NLPs.
Create your own Decision Tree regression project and score high accuracy , this project can help beginners in Machine learning - ML to do that with clear and easy steps.
A very good nanodegree program for those who have a strong background and strong knowledge in deep learning algorithms and wishful to grasp some practicatl hands-on experiences to implement deep learning advanced techniques with Pytorch
Realtime person's face recognize and can classify emotion using webcam, video or images.
Create your own ensemble tress regression - GBTR model and score high accuracy , this project can help beginners in Machine learning - ML to do that with clear and easy steps.
Gradient descent different types implemented from scratch. The project covers the Stochastic, Mini-batch, and Batch gradient descent with different types including; Ada-Grad, RMS-Prop, Adam, NAG, and Momentum-Based Gradient descent.
Data Camp Intermediate Python Course Certification