hadeer-34's Stars
RyersonAI/Breakout-DQN
rafael4512/Uminho
Projects done at the University of Minho
karthikbhamidipati/neural-linear-reinforcement-learning
Neural-linear features for value function approximation in ATARI games
HMUNACHI/halo
A Library That Uses Quantized Diffusion Model With Clustered Weights For Efficiently Generating More Image Datasets On-Device.
prabhatverma286/dana
bishetheanswer/deep-q-learning-tfg
Undergraduate Dissertation
marctuscher/DRQN-tensorflow
Deep recurrent Q Learning using Tensorflow, openai/gym and openai/retro
ofyildirim/pytorch-mnist-fashion-cnn
a repo for classifying mnist fashion dataset with cnn on pytorch
yunjhongwu/Double-DQN-Breakout
Playing Breakout with double deep Q network
SinanGncgl/Deep-Q-Network-AtariBreakoutGame
Playing Atari Breakout Game with Reinforcement Learning (DQN , Deep Q Learning)
Parsa33033/Deep-Reinforcement-Learning-DQN
Deep Reinforcement Learning with DQN, Double DQN, Dueling DQN, Noisy Net (Noisy DQN), and DQN with Prioritized Experience Replay
ShanHaoYu/Deep-Q-Network-Breakout
This is an implementation of Deep Q Learning (DQN) playing Breakout from OpenAI's gym with Keras.
noctrog/Breakout_DDQN
DDQN model learns to play Breakout
RahulBarman101/breakout-v0-ddqn
The atari breakout game from gym library played using a dueling DQN network or DDQN in short
andi611/DQN-Deep-Q-Network-Atari-Breakout-Tensorflow
Training a vision-based agent with the Deep Q Learning Network (DQN) in Atari's Breakout environment, implementation in Tensorflow.
karthikbhamidipati/dqn-atari-breakout
Keras implementation of deep-q-network for Atari breakout of OpenAI Gym.
caraevangeline/Machine_Learning_Coursework
abdul7gaffar/MACHINE-LEARNING
learn to train nueral networks. work on classifiers like logistic regression, Naive bayesian and liner classifiers
odeb1/GMM_EM-Algorithm
alexcaselli/Deep-Q-Network-Atari-Breakout
The purpose of this project is to train a Deep Q-Network agent (https://daiwk.github.io/assets/dqn.pdf) using the OpenAI Gym environment (https://gym.openai.com/) to play the famous Atari game BreakOut. The DQN agent has 3 main components: the online Q-network, the target Q-network, and a replay buffer.
dani-amirtharaj/Deep-Q-Learning
A program to train an agent on a simple tile based environment using deep Q-networks (Neural Networks and Q-learning) and a program to train an agent to play the Breakout ATARI game.
GiannisMitr/DQN-Atari-Breakout
A Deep Q-Network trained to play Breakout Atari game on OpenAI Gym environment.
otnemrasordep/gmm-phonemes
Final assignment for ECS708: Machine Learning. About unsupervised gaussian mixture models using the expectation-maximization algorithm.
AdrianHsu/breakout-Deep-Q-Network
Reinforcement Learning | tensorflow implementation of DQN, Dueling DQN and Double DQN performed on Atari Breakout
anmolsinghsuag/emotion_recognition
Facial Emotion Recognition using Convolutional Neural Networks
giannoier/Emotion-Recognition
Emotion Recognition from image with CNN
amogh7joshi/engagement-detection
Engagement Detection, including facial detection and emotion recognition, using CNNs/LSTMs.
soumyajit4419/Face_And_Emotion_Detection
Performing image classification for detection of various human emotions using CNN Architecture.
mayankchaudhary26/Emotion_Detection_CNN_keras
Train and test our algorithm using Convolution Neural Networks and classify emotions in real-time.
Carlloy/Recognition-of-emotions-using-CNN
Student project of e-Health system. Real-time recognition of emotions and pulse detection from webcam video.