Text Classification & Embeddings Visualization Using LSTMs, CNNs, and Pre-trained Word Vectors

[unable to retrieve full-text content]In this tutorial, I classify Yelp round-10 review datasets. After processing the review comments, I trained three model in three different ways and obtained three word embeddings.
Original Post: Text Classification & Embeddings Visualization Using LSTMs, CNNs, and Pre-trained Word Vectors

Overview and benchmark of traditional and deep learning models in text classification

[unable to retrieve full-text content]In this post, traditional and deep learning models in text classification will be thoroughly investigated, including a discussion into both Recurrent and Convolutional neural networks.
Original Post: Overview and benchmark of traditional and deep learning models in text classification

KDnuggets™ News 18:n24, Jun 20: Data Lakes – The evolution of data processing; Text Generation with RNNs in 4 Lines of Code

[unable to retrieve full-text content]How to spot a beginner Data Scientist; How To Create Natural Language Semantic Search For Arbitrary Objects With Deep Learning; Statistics, Causality, and What Claims are Difficult to Swallow: Judea Pearl debates Kevin Gray; Cartoon: FIFA World Cup Football and Machine Learning
Original Post: KDnuggets™ News 18:n24, Jun 20: Data Lakes – The evolution of data processing; Text Generation with RNNs in 4 Lines of Code

Generating Text with RNNs in 4 Lines of Code

[unable to retrieve full-text content]Want to generate text with little trouble, and without building and tuning a neural network yourself? Let’s check out a project which allows you to “easily train your own text-generating neural network of any size and complexity on any text dataset with a few lines of code.”
Original Post: Generating Text with RNNs in 4 Lines of Code

On the contribution of neural networks and word embeddings in Natural Language Processing

[unable to retrieve full-text content]In this post I will try to explain, in a very simplified way, how to apply neural networks and integrate word embeddings in text-based applications, and some of the main implicit benefits of using neural networks and word embeddings in NLP.
Original Post: On the contribution of neural networks and word embeddings in Natural Language Processing