Ramez Shendy's repositories
TSP-Genetic-Algorithm
This repository provides a solution to the classic Traveling Salesman Problem (TSP) using a genetic algorithm. The genetic algorithm is a heuristic optimization method inspired by the process of natural selection and genetic variation.
Few-shot-satellite-image-classification-OPS-SAT
Few-shot satellite image classification for bringing deep learning on board OPS-SAT
Classification
Prediction and Evaluation to different classification Algorithms
ROBO1x-Robotics-fundamentals
Robotics micro-masters first course
Startups-DataSet
Exploratory and Predictive Analysis for 50 Startups Across USA
Clustering
Clustering Algorithms with helpful visualization and intuitions
Data-Science--Cheat-Sheet
Cheat Sheets
Deep-Learning-Andrew-NG
Andrew NG Course on Deep Learning
deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
deeplearning-models
A collection of various deep learning architectures, models, and tips
Dimensionality-Reduction
for visualizing data
insightface
Face Analysis Project on MXNet
MNIST-Kaggle-Digit-Recognizer-0.996
Implementation of MNIST classification using Multi Layer fully connected network and Constitutional Neural network
NNets2020
Artificial neural networks and deep learning course
RecSysClassPG23
Introduction to RecSys for Politechnika Gliwicka Y23
Repo-2017
Python codes in Machine Learning, NLP, Deep Learning and Reinforcement Learning with Keras and Theano
Repo-2018
Deep Learning Summer School + Tensorflow + OpenCV cascade training + YOLO + COCO + CycleGAN + AWS EC2 Setup + AWS IoT Project + AWS SageMaker + AWS API Gateway + Raspberry Pi3 Ubuntu Core
Repo-2019
AWS RDS, AWS Forecast, EMR Spark Cluster, Hive, Serverless, Google Assistant + Raspberry Pi, Infrared, Google Cloud Platform Natural Language, Anomaly detection, Mind Controlled Apparatus, Tensorflow, Mathematics
Sentiment-Analysis
contains Arabic Sentiment Analysis for Arabic Book reviews
Titanic-Data-Set-Kaggle-0.803-submission-Accuracy
Titanic: Machine Learning from disaster (Kaggle) 0.803 submission accuracy. using 7 prediction models and ensemble learning Hard Voting with weights.