ramyalsharif

ramyalsharif's Stars

• deepfakes/faceswap

  Deepfakes Software For All

  Language:Python52.8k1.5k86813.3k

• aymericdamien/TensorFlow-Examples

  TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

  Language:Jupyter Notebook43.5k2k23614.9k

• dwmkerr/hacker-laws

  💻📖 Laws, Theories, Principles and Patterns that developers will find useful. #hackerlaws

  Language:Shell25.9k4382051.5k

• rasbt/deeplearning-models

  A collection of various deep learning architectures, models, and tips

  Language:Jupyter Notebook16.8k595304k

• brightmart/text_classification

  all kinds of text classification models and more with deep learning

  Language:Python7.9k2991242.6k

• zihangdai/xlnet

  XLNet: Generalized Autoregressive Pretraining for Language Understanding

  Language:Python6.2k1702631.2k

• ibab/tensorflow-wavenet

  A TensorFlow implementation of DeepMind's WaveNet paper

  Language:Python5.4k2622781.3k

• buriburisuri/speech-to-text-wavenet

  Speech-to-Text-WaveNet : End-to-end sentence level English speech recognition based on DeepMind's WaveNet and tensorflow

  Language:Python4k197117793

• minimaxir/gpt-2-simple

  Python package to easily retrain OpenAI's GPT-2 text-generating model on new texts

  Language:Python3.4k74263675

• guillaume-chevalier/LSTM-Human-Activity-Recognition

  Human Activity Recognition example using TensorFlow on smartphone sensors dataset and an LSTM RNN. Classifying the type of movement amongst six activity categories - Guillaume Chevalier

  Language:Jupyter Notebook3.4k16141938

• automagica/automagica

  AI-powered Smart Robotic Process Automation 🤖

  Language:Python3k122112479

• anfederico/clairvoyant

  Software designed to identify and monitor social/historical cues for short term stock movement

  Language:Python2.4k15231767

• openai/generating-reviews-discovering-sentiment

  Code for "Learning to Generate Reviews and Discovering Sentiment"

  Language:Python1.5k24051380

• yunjey/show-attend-and-tell

  TensorFlow Implementation of "Show, Attend and Tell"

  Language:Jupyter Notebook9063886325

• mozilla/DeepSpeech-examples

  Examples of how to use or integrate DeepSpeech

  Language:Python8282691351

• aqibsaeed/Multilabel-timeseries-classification-with-LSTM

  Tensorflow implementation of paper: Learning to Diagnose with LSTM Recurrent Neural Networks.

  Language:Jupyter Notebook576399187

• dennybritz/rnn-tutorial-gru-lstm

  Language Model GRU with Python and Theano

  Language:Python4993912220

• zweigraf/face-landmarking-ios

  👦 Basic face landmarking on iPhone with Dlib via Swift & ObjC++

  Language:C++4812736125

• akaraspt/deepsleepnet

  DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG

  Language:Python4162046158

• RobRomijnders/LSTM_tsc

  An LSTM for time-series classification

  Language:Python4103516146

• aj-4/tinder-swipe-bot

  Language:Python4033023180

• TNTLFreiburg/braindecode

  Outdated, see new https://github.com/braindecode/braindecode

  Language:Python3243163155

• nmhkahn/pytorch-exercise

  Practical Exercise Codes for PyTorch

  Language:Jupyter Notebook27114452

• tthustla/efficient_frontier

  Markowitz portfolio optimisation (efficient frontier) in Python

  Language:Jupyter Notebook19112374

• philipperemy/tensorflow-multi-dimensional-lstm

  Multi dimensional LSTM as described in Alex Graves' Paper https://arxiv.org/pdf/0705.2011.pdf

  Language:Jupyter Notebook15512546

• weilheim/EEG

  PyTorch EEG emotion analysis using DEAP dataset

  Language:Python763232

• mratsim/McKinsey-SmartCities-Traffic-Prediction

  Adventure into using multi attention recurrent neural networks for time-series (city traffic) for the 2017-11-18 McKinsey IronMan (24h non-stop) prediction challenge

  Language:Jupyter Notebook583127

• libgdx/gdx-realsense

  RealSense support for libGDX

  Language:C++52231028

• paulmorio/deap_analysis

  DEAP Dataset Analysis Code

  Language:Jupyter Notebook492211

• TheRDavid/RealSense

  Recognize emotions with the intel realsense sr300

  Language:HTML8417