Tareq Tayeh's repositories
AROM-DRL_Adaptive-Routing-Optimization-for-QoS-aware-SDNs-using-Deep-Reinforcement-Learning
The purpose of this project is to introduce an Adaptive RO Model for QoS-aware SDNs using DRL that dynamically considers various QoS parameters to generate a dynamic action-reward strategy.
Anomaly-Detection-with-CNNs-for-Industrial-Surface-Inspection
Paper replication for B. Staar et al “Anomaly detection with convolutional neural networks for industrial surface inspection,” Procedia CIRP, vol. 79, pp. 484–489, 2019.
Simple-TimeSeries-Forecasting-Using-Different-ML-Models
Simple forecasting of Canada's CO2 Emissions using Linear Regression, Support Vector Regression, Gaussian Process Regression, and Boosted Regression Tree Ensemble.
Price-TimeSeries-Anomaly-Detection-with-LSTM-Autoencoders-Keras
Detecting anomalies in GE stock price data using an LSTM Autoencoder
Coursera-Deeplearning.ai-DeepLearningSpecialization-HandwrittenNotes
My handwritten notes for https://www.coursera.org/specializations/deep-learning.
Heart-Disease-Diagnosis-using-ML-Ensemble-Methods
The purpose of this project is to accurately diagnose heart disease using different machine learning techniques and classifiers, including ensemble methods.
Mininet-Simulation-with-Floodlight
The purpose of this program is to simulate a simple Mininet network connected to a Floodlight SDN controller and to extract valuable QoS metrics from the iperf and ping commands.
Skin-Lesion-Classification-using-CNN
The purpose of this project is to correctly classify the skin lesion category present in an image, by building the most accurate ML model. 4 different CNN architectures were used and evaluated.
3DObjectsShade
The purpose of this program is to design and implement a program that allows a user to shade objects (spheres, cones, and torii) in various colours. The program should scale the parametric objects within a scene (using 3D homogeneous transformation matrices) and render them using a simple Lambertian shading model that assumes diffuse light reflection from objects.
Building-A-Statistical-Based-And-LSTM-Based-Anomaly-Detection-Algorithm
The purpose of this program is to detect anomalies in real-life time series data by building (and evaluating) a gaussian-based Anomaly Detection (AD) algorithm and an LSTM-based AD algorithm.
PlantsvsZombies
Done with C++ on Qt-Creator
3DTorusAndSphere
Creating and rendering 3D wiremesh objects with the use of Bresenham's algorithm for 2D line segments, the synthetic camera, and the parametric functions for the sphere and the torus.
Coursera-Deeplearning.ai-AIForMedicineSpecialization-HandwrittenNotes
My handwritten notes for https://www.coursera.org/specializations/ai-for-medicine
Coursera-IBM-MachineLearningWithPython-HandwrittenNotes
My notes for https://www.coursera.org/learn/machine-learning-with-python
Coursera-Stanford-MachineLearning-HandwrittenNotes
My notes for https://www.coursera.org/learn/machine-learning
Machine_Learning_Course_Anomaly_Detection_Final_Exam
The purpose of this program (Exam) is to detect anomalies in time series data using various Machine Learning techniques and models.
RayTracer
The purpose of this program is to non-recursively ray-trace images of scenes containing a number of simple generic objects and must be able to must be able to: - Render spheres and planes as generic objects - Implement shading (ambient, diffuse, and specular reflections) - Implement shadowing through the use of shadow rays
RSA-Signature
RSA file signature
WesternUniversity-ECE9603A-DataAnalytics-HandwrittenNotes
My notes for ECE9603A Data Analytics course offered at Western University [Fall 2019]