Tags » Embeddings

Embedding Layers, Autoencoders and High Dimensional Forecasting


This post will illustrate how to use Neural Networks to do dimensionality reduction and generate usable factors. I will first discuss methods typically used in machine learning for dimensionality reduction: PCA regression, LASSO, and Ridge Regression. 6,799 more words


Code: Word2Vec in Spark

Here is a snippet that might be useful to you if you are looking to implement Word2Vec and save the embeddings of the trained model. I’ve added types to the variables as well as to some placeholder names to make it easier to understand what is expected as an input to various functions… 295 more words