mshadloo

Neural-Machine-Translation-with-Attention

I implement encoder-decoder based seq2seq models with attention using Keras. The encoder can be a Bidirectional LSTM, a simple LSTM, or a GRU, and the decoder can be an LSTM or a GRU. I evaluate the models on an English-French dataset.

Algorithm

Codes of Cracking the Coding Interview, 6th Edition 189 Programming Questions and Solutions

deep-learning-coursera

Deep Learning Specialization by Andrew Ng on Coursera.

Deep-Neural-Network-from-scratch

Deep neural network model on top of Tensorflow

Gender-Detection-with-Decision-Tree-from-scrach

In this repo, I implement a decision tree classifier from scratch using python and pandas. I use this decision tree to detect gender based on names. I use the first letter, first two letters, first three letters, last letter, last two letters, last three letters, etc. as features.

genderDetection

Logistic-regression

Logistic regression with neural network mindset using numpy

Recommendation-system

I implement I-AutoRec (an autoencoder framework for collaborative filtering b) with Keras and tuned hyperparameters of this model using a validation set.

Resnet_cifar10_pytorch

In this repo, I implemented ResNet for CIFAR10 as described in the original paper with Pytorch

Web-Application-with-Django-for-Object-Identification

In this repo, I use Django to create a web application and I use TensorFlow as the backend to do object identification. I deploy my project on AWS Lighsail.

MLP-LogisticRegression-DecisionTree-from-scratch

mshadloo

Config files for my GitHub profile.

mshadloo.github.io

ResidualNetwork

Residual network with keras for CIFAR10

ResNet_CIFAR10

Reproducing CIFAR10 experiment results from the original ResNet paper using Pytorch in IPython notebook.