Getting started with OpenAI GPT-2

GPT-2 was released by OpenAI last year: Better Language Models and Their Implications, and the related code was released on Github: Code for the paper “Language Models are Unsupervised Multitask Learners” . First install OpenAI GPT-2 from github, my pc … Continue reading →

Dive into NLP with Deep Learning, Part I: Getting Started with DL4NLP

Before diving into the Natural Language Processing with Deep Learning, you should know something about them. Here is a list of related books and courses for you: 1. Deep Learning Specialization by Andrew Ng We especially recommended this specialization for … Continue reading →

Update Korean, Russian, French, German, Spanish Wikipedia Word2Vec Model for Word Similarity

I have launched WordSimilarity on April, which focused on computing the word similarity between two words by word2vec model based on the Wikipedia data. The website has the English Word2Vec Model for English Word Similarity: Exploiting Wikipedia Word Similarity by … Continue reading →

Dive Into NLTK, Part XI: From Word2Vec to WordNet

This is the eleventh article in the series “Dive Into NLTK“, here is an index of all the articles in the series that have been published to date: Part I: Getting Started with NLTK Part II: Sentence Tokenize and Word … Continue reading →

Exploiting Wikipedia Word Similarity by Word2Vec

We have written “Training Word2Vec Model on English Wikipedia by Gensim” before, and got a lot of attention. Recently, I have reviewed Word2Vec related materials again and test a new method to process the English wikipedia data and train Word2Vec … Continue reading →

Dive Into NLTK, Part X: Play with Word2Vec Models based on NLTK Corpus

This is the tenth article in the series “Dive Into NLTK“, here is an index of all the articles in the series that have been published to date: Part I: Getting Started with NLTK Part II: Sentence Tokenize and Word … Continue reading →

Dive Into NLTK, Part IX: From Text Classification to Sentiment Analysis

This is the ninth article in the series “Dive Into NLTK“, here is an index of all the articles in the series that have been published to date: Part I: Getting Started with NLTK Part II: Sentence Tokenize and Word … Continue reading →

Deep Learning for NLP resources from Github

Two list of “Deep Learning for NLP resources” from github, just for reference: Deep Learning for NLP resources: Introductory and state of the art resources for NLP sequence modeling tasks like dialog. from https://github.com/andrewt3000/DL4NLP Deep-Learning-for-NLP-Resources: List of resources to get … Continue reading →

Getting Started with Keyword Extraction

Recently, I have surveyed some keyword extraction tools, papers and documents, and record them here for getting started with keyword extraction. According wikipedia, Keyword Extraction is defined like this: Keyword extraction is tasked with the automatic identification of terms that … Continue reading →

Deep Learning for Text Mining from Scratch

Here is a list of courses or materials for you to learn deep learning for text mining from scratch。 Especially recommended Deep Learning Specialization by Andrew Ng About This Specialization If you want to break into AI, this Specialization will … Continue reading →