Building Recurrent Neural Networks in Tensorflow

Building Recurrent Neural Networks in Tensorflow Recurrent Neural Nets (RNN) detect features in sequential data (e.g. time-series data). Examples of applications which can be made using RNN’s are anomaly detection in time-series data, classification of ECG and EEG data, stock market prediction, speech recogniton, sentiment analysis, etc. This is done by unrolling the data into N different copies of

Read Full Story

Using Convolutional Neural Networks to detect features in sattelite images

Using Convolutional Neural Networks to detect features in sattelite images In a previous blog post we have seen how to build Convolutional Neural Networks (CNN) in Tensorflow, by building various CNN architectures (like LeNet5, AlexNet, VGGNet-16) from scratch and training them on the MNIST, CIFAR-10 and Oxflower17 datasets. It starts to get

Read Full Story