Long Short-Term Memory (LSTM) Recurrent Neural Networks are a powerful type of deep learning suited for sequence prediction problems.

A possible concern when using LSTMs is if the added complexity of the model is improving the skill of your model or is…

Learning SVMs from examples

A TensorBoard plugin for visualizing arbitrary tensors in a video as your network trains. - chrisranderson/beholder

w-net: a convolutional neural network architecture for the self-supervised learning of depthmap from pairs of stereo images. - LouisFoucard/w-net

Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow - GitHub - omimo/xRBM: Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow

There are wide applications of neural networks in industry. This post is an attempt to intuitively explain one of the applications of word2vec in retail indust

The ultimate guide to machine learning. Simple, plain-English explanations accompanied by math, code, and real-world examples.

Source of latest credible papers, videos and projects on machine learning for scientists and engineers.

Python module + R package to predict the reactions to a given text using a pretrained recurrent neural network. - minimaxir/reactionrnn

Project #1: An app for the visually impaired that describes your surroundings in plain English Project #2: Vision system for autonomous vehicles Project #3: ...

Gentle introduction to the Stacked LSTM
with example code in Python.
The original LSTM model is comprised of a single hidden LSTM layer followed by a standard feedforward output layer.

The Stacked LSTM is an extension to this model that has multiple…

Как известно, в IT мужчин значительно больше, чем женщин, хотя последние зачастую не уступают по знаниям и навыкам. По нашим наблюдениям, в сфере Data Science эт...

The BAIR Blog

In many real-world Machine Learning projects, there is a need to ensemble complex models as well as maintain pipelines.