Pinned Repositories
3D-Machine-Learning
A resource repository for 3D machine learning
abstractive-text-summarization
PyTorch implementation/experiments on Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond paper.
Awesome-Mobility-Machine-Learning-Contents
Machine Learning / Deep Learning Contents in Mobility Industry(Transportation)
awesome-multimodal-ml
Reading list for research topics in multimodal machine learning
crop_yield_prediction
Crop Yield Prediction with Deep Learning
cs581-database-management
This project evaluates ride-sharing algorithms on spatio-temporal data. The data in this case represents nearly 700 million trips in New York City.
DAgger
Reinforcement Learning -- Imitation Learning, Behavior Cloning, DAgger (Data Aggregation)
Deep-Learning-Cheat-Sheets
Cheat Sheet - RNN and CNN
Distracted-Driver-Detection
Final Report
Referring-Expression-Generation-and-Comprehension-
Research Paper
be-redAsmara's Repositories
be-redAsmara/Distracted-Driver-Detection
Final Report
be-redAsmara/Referring-Expression-Generation-and-Comprehension-
Research Paper
be-redAsmara/3D-Machine-Learning
A resource repository for 3D machine learning
be-redAsmara/abstractive-text-summarization
PyTorch implementation/experiments on Abstractive Text Summarization using Sequence-to-sequence RNNs and Beyond paper.
be-redAsmara/Awesome-Mobility-Machine-Learning-Contents
Machine Learning / Deep Learning Contents in Mobility Industry(Transportation)
be-redAsmara/awesome-multimodal-ml
Reading list for research topics in multimodal machine learning
be-redAsmara/crop_yield_prediction
Crop Yield Prediction with Deep Learning
be-redAsmara/cs581-database-management
This project evaluates ride-sharing algorithms on spatio-temporal data. The data in this case represents nearly 700 million trips in New York City.
be-redAsmara/DAgger
Reinforcement Learning -- Imitation Learning, Behavior Cloning, DAgger (Data Aggregation)
be-redAsmara/Deep-Learning-Cheat-Sheets
Cheat Sheet - RNN and CNN
be-redAsmara/deepul
be-redAsmara/devops-master-class
Learn Devops with Docker, Kubernetes, Terraform, Ansible, Jenkins and Azure Devops
be-redAsmara/fairseq-transliteration.ipynb
be-redAsmara/gans-in-action
Companion repository to GANs in Action: Deep learning with Generative Adversarial Networks
be-redAsmara/graph-based-deep-learning-literature
links to conference publications in graph-based deep learning
be-redAsmara/IROS2019-paper-list
IROS2019 paper list from PaopaoRobot
be-redAsmara/lara2018
This repository is intended to develop the work supported by the Latin America Research Awards 2018.
be-redAsmara/learn
Neuro-symbolic interpretation learning (mostly just language-learning, for now)
be-redAsmara/lowresource-nlp-bootcamp-2020
The website for the CMU Language Technologies Institute low resource NLP bootcamp 2020
be-redAsmara/machine_learning_examples
A collection of machine learning examples and tutorials.
be-redAsmara/nn4nlp-code
Code Samples from Neural Networks for NLP
be-redAsmara/NSCL-PyTorch-Release
PyTorch implementation for the Neuro-Symbolic Concept Learner (NS-CL).
be-redAsmara/probnmn-clevr
Code for ICML 2019 paper "Probabilistic Neural-symbolic Models for Interpretable Visual Question Answering" [long-oral]
be-redAsmara/PySyft
A library for encrypted, privacy preserving machine learning
be-redAsmara/pytorch-Deep-Learning
Deep Learning (with PyTorch)
be-redAsmara/pytorch-seq2seq
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText. [IN PROGRESS]
be-redAsmara/SDE
Source code for the paper "Multilingual Neural Machine Translation with Soft Decoupled Encoding"
be-redAsmara/speaker_listener_reinforcer
Torch Implementation of Speaker-Listener-Reinforcer for Referring Expression Generation and Comprehension
be-redAsmara/stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.
be-redAsmara/tydiqa
TyDi QA contains 200k human-annotated question-answer pairs in 11 Typologically Diverse languages, written without seeing the answer and without the use of translation, and is designed for the training and evaluation of automatic question answering systems. This repository provides evaluation code and a baseline system for the dataset.