This contains the codes of deep neural network on different datasets using tensorflow.
In this code I have trained the convolution neural network on mnist dataset and got the accuracy ~98.5%.
In this code I have made a deep neural network having three hidden layers using tensorflow.After this we train our model on mnist dataset which contains images of numbers(0-9) of 28*28 pixels.We got accuracy of ~95%.
In this code I have trained the convolution neural network on mnist dataset and got the accuracy ~97%.
In this code I have trained the convolution neural network on mnist dataset and got the accuracy ~98.5%.
In this code we deal with the realistic dataset.In this we are converting the data into vectors which we can train in our neural network made in mnist_tensorflow.py .
In this code I use the vectors made in create_sentiment_featuresets.py and neural network of neural_net_mnist.py.In this we got accuracy of ~68%. It has so low accuracy because of very less data.It can achieve high accuracy if we have larger dataset.
In this code I have done sentiment analysis on realistic data which is quite large using deep neural network.
This contains the codes of deep neural network on different datasets using tflearn.
In this code I have trained the convolution neural network on mnist dataset and got the accuracy ~98%.