Short technical information about Word2Vec, GloVe and Fasttext
Introduction
nlp
Evolution of Language Models: N-Grams, Word Embeddings, Attention & Transfo
This post collates research on the advancements of Natural Language Processing (NLP) over the years.
Good Grams: How to Find Predictive N-Grams for your Problem
Figuring out what words are predictive for your problem is easy!
Natural Language Processing Recipes: Best Practices and Examples
Here is an overview of another great natural language processing resource, this time from Microsoft, which demonstrates best practices and implementation guidelines for a variety of tasks and scenarios.
Python Libraries for Natural Language Processing - Towards Data Science
An Overview Of popular python libraries for Natural Language Processing
The Cost of Training NLP Models: A Concise Overview
We review the cost of training large-scale language models, and the drivers of these costs. The intended audience includes engineers and scientists budgeting their model-training experiments, as...
Twitter Sentiment Analysis with Node.js
How people are talking about your brand
Topic Modeling Articles with NMF
Extracting topics is a good unsupervised data-mining technique to discover the underlying relationships between texts. There are many…
TLDR This - Article Summarizer & Online Text Summarizing Tool
TLDR This is a Free online text summarizing tool that automatically condenses long articles, documents, essays, or papers into key summary paragraphs using state-of-the-art AI.
google-research/bert: TensorFlow code and pre-trained models for BERT
TensorFlow code and pre-trained models for BERT.
The Illustrated BERT, ELMo, and co. (How NLP Cracked Transfer Learning) – J
Discussions: Hacker News (98 points, 19 comments), Reddit r/MachineLearning (164 points, 20 comments) Translations: Chinese (Simplified), French 1, French 2, Japanese, Korean, Persian, Russian, Spanish 2021 Update: I created this brief and highly accessible video intro to BERT…
[Project] nlp-tutoral repository who is studying NLP(Natural Language Proce
219 votes, 26 comments. Hello. This is my first post in reddit I created nlp-tutoral repository who is studying NLP(Natural Language Processing)…
Why BERT Fails in Commercial Environments - Intel AI
Build a BERT Sci-kit Transformer
BERT can get you state-of-the-art results on many NLP tasks and it only takes a few lines of code.
Vincent Boucher on LinkedIn: #transformer #bert #nlp
Pre-training SmallBERTa - A tiny model to train on a tiny dataset An end to end colab notebook that allows you to train your own LM (using HuggingFace…
The Big Bad NLP Database: Access Nearly 300 Datasets
Check out this database of nearly 300 freely-accessible NLP datasets, curated from around the internet.
Beating the baseline recommender using Graph and NLP techniques in PyTorch
Decoding NLP Attention Mechanisms
Arguably more famous today than Michael Bay’s Transformers, the transformer architecture and transformer-based models have been breaking all kinds of state-of-the-art records. They are (rightfully) getting the attention of a big portion of the deep learning community and…
Over 150 of the Best Machine Learning, NLP, and Python Tutorials I’ve Found
By popular demand, I’ve updated this article with the latest tutorials from the past 12 months. Check it out here
Quick Introduction to Sentiment Analysis
What is sentiment analysis, how to perform it, and how it can help your business.
A Comprehensive Guide to Natural Language Generation
Follow this overview of Natural Language Generation covering its applications in theory and practice. The evolution of NLG architecture is also described from simple gap-filling to dynamic document creation along with a summary of the most popular NLG models.
How to train a new language model from scratch using Transformers and Tokenizers
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
A list of beginner-friendly NLP projects–using pre-trained models
Build software with machine learning — no math required.
Top NLP Research Papers With Business Applications From ACL 2019
This year’s annual meeting of the Association for Computational Linguistics (ACL 2019) was bigger than ever. Although the conference received 75% more submissions than last year, the quality of the research papers remained high, and so the acceptance rates are almost the same…
Exploratory Data Analysis for Natural Language Processing: A Complete Guide to Python Tools
Explore NLP EDA with Python tools: learn about text statistics, ngrams, topic modeling with pyLDAvis, sentiment analysis, and more
[N] HuggingFace releases ultra-fast tokenization library for deep-learning
336 votes, 25 comments. Huggingface, the NLP research company known for its transformers library, has just released a new open-source library for…
An Introductory Guide to NLP for Data Scientists with 7 Common Techniques
Data Scientists work with tons of data, and many times that data includes natural language text. This guide reviews 7 common techniques with code examples to introduce you the essentials of NLP, so you can begin performing analysis and building models from textual data.
Turing-NLG: A 17-billion-parameter language model by Microsoft
This figure was adapted from a similar image published in DistilBERT. Turing Natural Language Generation (T-NLG) is a 17 billion parameter language model by Microsoft that outperforms the state of the art on many downstream NLP tasks. We present a demo of the model, including…
Top NLP Algorithms & Concepts - DataScienceCentral.com
Today, one of the most popular tasks in Data Science is processing information presented in the text form. Exactly this is text representation in the form of mathematical equations, formulas, paradigms, patterns in order to understand the text semantics (content) for its further…
10 Common NLP Terms Explained for the Text Analysis Novice - DataScienceCentral.com
If you’re relatively new to the NLP and Text Analysis world, you’ll more than likely have come across some pretty technical terms and acronyms, that are challenging to get your head around, especially, if you’re relying on scientific definitions for a plain and simple…
Serving GPT-2 in Google Cloud Platform
A CloudOps Journey
nlp-recipes/README.md at master · microsoft/nlp-recipes
Natural Language Processing Best Practices & Examples - microsoft/nlp-recipes
Lit BERT: NLP Transfer Learning In 3 Steps - Towards Data Science
In this tutorial we learn to quickly train Huggingface BERT using PyTorch Lightning for transfer learning on any NLP task
Hugging Face – The AI community building the future.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
BERT Explained: A Complete Guide with Theory and Tutorial
Unless you have been out of touch with the Deep Learning world, chances are that you have heard about BERT — it has been the talk of the town for the last one year. At the end of 2018 researchers …
How ‘Embeddings’ Encode What Words Mean — Sort Of
Machines work with words by embedding their relationships with other words in a string of numbers.
Deconstructing BERT: Distilling 6 Patterns from 100 Million Parameters
From BERT’s tangled web of attention, some intuitive patterns emerge.
Advanced NLP with spaCy · A free online course
spaCy is a modern Python library for industrial-strength Natural Language Processing. In this free and interactive online course, you'll learn how to use spaCy to build advanced natural language understanding systems, using both rule-based and machine learning approaches.
Text Analytics
Medallia's text analytics software tool provides actionable insights via customer and employee experience sentiment data analysis from reviews & comments.
A tour of awesome features of spaCy (part 1/2) – Eliiza-AI – Medium
A few weeks ago I started working on a text summarisation project and I needed a Natural Language Processing library with comprehensive…
Word2vec: fish music = bass | graceavery
A tour of awesome features of spaCy (part 2/2) - Eliiza-AI - Medium
In the first part of this overview of spaCy we went over the features of the large English pretrained model that spaCy comes with. In this…
Introducing spaCy v2.1 · Blog · Explosion AI
Version 2.1 of the spaCy Natural Language Processing library includes a huge number of features, improvements and bug fixes. In this post, we highlight some of the things we're especially pleased with, and explain some of the most challenging parts of preparing this big release.
The Illustrated Word2vec
Discussions: Hacker News (347 points, 37 comments), Reddit r/MachineLearning (151 points, 19 comments) Translations: Chinese (Simplified), French, Korean, Portuguese, Russian “There is in all things a pattern that is part of our universe. It has symmetry, elegance, and grace…
Measuring the varied sentiments of good and bad words
There was a survey a while back that asked people to provide a 0 to 100 percent value to probabilistic words like “usually” and “likely”. YouGov did something similar for wo…
[P] Using T-SNE and word2vec embeddings to create clusters in wordclouds
2.9M subscribers in the MachineLearning community. Beginners -> /r/mlquestions , AGI -> /r/singularity, career advices -> /r/cscareerquestions…
mukund109/word-mesh: A context-preserving word cloud generator
A context-preserving word cloud generator.
Emotion and Sentiment Analysis: A Practitioner’s Guide to NLP
Sentiment analysis is widely used, especially as a part of social media analysis for any domain, be it a business, a recent movie, or a product launch, to understand its reception by the people and what they think of it based on their opinions or, you guessed it, sentiment!
NLP's ImageNet moment has arrived
The time is ripe for practical transfer learning to make inroads into NLP.
Deep Meaning Beyond Thought Vectors
I ended my last post by saying that I might write a follow-up post on current work that seems to exhibit progress toward natural language understanding. I am going to discuss a couple sampled pap…