relanwar
Research scientist, interested in image processing, computer vision and machine learning.
Electronics Research InstituteEgypt
Pinned Repositories
cd0385-project-starter
deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
Doc_samples
Faces_Generation_using_GANs
Generating people faces using Deep Convolutional Generative Adversarial Networks (DCGAN) This project is about generating fake people faces using GANs using a dataset of celebreties faces "CelebFaces Attributes Dataset (CelebA)". The model generated samples should look like fairly realistic faces with small amounts of noise. This project is the fourth requirement to graduate from Udacity's Deep learning Nano-degree.
Generating_TV_scipts_using_RNN
Generating TV scipts using Recurrent Neural Networks (RNN) This project is about generating self Seinfeld TV scripts using RNNs using a Seinfeld dataset of scripts from 9 seasons. The Neural Network generates a new, "fake" TV script. This project is the third requirement to graduate from Udacity's Deep learning Nano-degree.
Introduction_to_Numpy_for_Linear_Algebra
This notebook has the basics of Numpy library for Linear Algebra's vector-matrix operations
Model_deployment_using_AWS
The deployment project is intended to be done using Amazon's SageMaker platform. In this project there is a working notebook instance which presents Sentiment analysis of IMDB movie reviews dataset using LSTM model which we are going to deploy on high level and low level, and test it using a web app service (HTTP POST) via an endpoint (LAMBDA function + API gateway) This project is the fifth requirement to graduate from Udacity's Deep learning Nano-degree.
Predicting_bike_rental_ridership
This project is about building a neural network from scratch to carry out a prediction problem on a real dataset! By building a neural network from the ground up, a much better understanding of gradient descent, backpropagation, and other concepts is gained. This project is the first requirement to graduate Udacity's Deep learning Nano-degree.
Predicting_landmarks_using_CNN
This project (nd101-c2-landmarks-starter) is about using Convolutional Neural Network (CNN) module to build a landmark classifier. The model should automatically be able to predict the location of the image based on any landmarks depicted in the image. This project is the second requirement to graduate from Udacity's Deep learning Nano-degree.
Probability_using_numpy_scipy
These notebooks contain probability computations using python and libraries like Numpy/scipy
relanwar's Repositories
relanwar/Introduction_to_Numpy_for_Linear_Algebra
This notebook has the basics of Numpy library for Linear Algebra's vector-matrix operations
relanwar/cd0385-project-starter
relanwar/deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
relanwar/Doc_samples
relanwar/Faces_Generation_using_GANs
Generating people faces using Deep Convolutional Generative Adversarial Networks (DCGAN) This project is about generating fake people faces using GANs using a dataset of celebreties faces "CelebFaces Attributes Dataset (CelebA)". The model generated samples should look like fairly realistic faces with small amounts of noise. This project is the fourth requirement to graduate from Udacity's Deep learning Nano-degree.
relanwar/Generating_TV_scipts_using_RNN
Generating TV scipts using Recurrent Neural Networks (RNN) This project is about generating self Seinfeld TV scripts using RNNs using a Seinfeld dataset of scripts from 9 seasons. The Neural Network generates a new, "fake" TV script. This project is the third requirement to graduate from Udacity's Deep learning Nano-degree.
relanwar/Model_deployment_using_AWS
The deployment project is intended to be done using Amazon's SageMaker platform. In this project there is a working notebook instance which presents Sentiment analysis of IMDB movie reviews dataset using LSTM model which we are going to deploy on high level and low level, and test it using a web app service (HTTP POST) via an endpoint (LAMBDA function + API gateway) This project is the fifth requirement to graduate from Udacity's Deep learning Nano-degree.
relanwar/Predicting_bike_rental_ridership
This project is about building a neural network from scratch to carry out a prediction problem on a real dataset! By building a neural network from the ground up, a much better understanding of gradient descent, backpropagation, and other concepts is gained. This project is the first requirement to graduate Udacity's Deep learning Nano-degree.
relanwar/Predicting_landmarks_using_CNN
This project (nd101-c2-landmarks-starter) is about using Convolutional Neural Network (CNN) module to build a landmark classifier. The model should automatically be able to predict the location of the image based on any landmarks depicted in the image. This project is the second requirement to graduate from Udacity's Deep learning Nano-degree.
relanwar/Probability_using_numpy_scipy
These notebooks contain probability computations using python and libraries like Numpy/scipy
relanwar/Randa_Elanwar
Config files for my GitHub profile.