NLP News Cypher | 01.19.20
Author(s): Ricky Costa Originally published on Towards AI. Photo by Robert Murray on Unsplash NLP News Cypher U+007C 01.19.20 Towards AI and Infinity And…. we’re back! What a week! First, we are happy to announce we are now publishing our weekly blog …
NLP Dataset Library
Author(s): Ricky Costa Originally published on Towards AI. Forget PIP, Conda, requirements.txt! Use Poetry Instead And Thank Me Later Bex T. in Towards AI Pain-free dependency management is finally here·8 min read·Jun 24 1.4K 17 … Read the full blog for free …
A Lite BERT for Reducing Inference Time
Author(s): Edward Ma Originally published on Towards AI. BERT Photo by Ksenia Makagonova on Unsplash BERT (Devlin et al., 2018) achieved lots of state-of-the-art results in 2018. However, it is not easy to use BERT (Devlin et al., 2018) in production even …
Adversarial Attacks in Textual Deep Neural Networks
Author(s): Edward Ma Originally published on Towards AI. What is an adversarial attack? Photo by Solal Ohayon on Unsplash Adversarial examples aim at causing target model to make a mistake on prediction. It can be either be intended or unintended to cause …
A Robustly Optimized BERT Pretraining Approach
Author(s): Edward Ma Originally published on Towards AI. What is BERT? Top highlight BERT (Devlin et al., 2018) is a method of pre-training language representations, meaning that we train a general-purpose “language understanding” model on a large text corpus (like Wikipedia), and …
Text Mining in Python: Steps and Examples
Author(s): Dhilip Subramanian In today’s scenario, one way of people’s success is identified by how they are communicating and sharing information with others. That’s where the concepts of language come into the picture. However, there are many languages in the world. Each …
Address Limitation of RNN in NLP Problems by Using Transformer-XL
Author(s): Edward Ma Originally published on Towards AI. Limitations of recurrent neural networks Photo by Joe Gardner on Unsplash Recurrent Neural Network (RNN) offers a way to learn a sequence of inputs. The drawback is that it is difficult to optimize due …
Prerequisites
Author(s): Thomas Kraehe Originally published on Towards AI. Top highlight Using Google Cloud’s Machine Learning as a Service U+007C Towards AI Analyzing the Mood of Chat Messages with Google Cloud’s Natural Language API With the help of NLP services like the Natural …
Unified Language Model Pre-training for Natural Language Understanding and Generation
Author(s): Edward Ma Originally published on Towards AI. Using UNILM to tackle natural language understanding (NLU) and natural language generation (NLG) Photo by Louis Hansel on Unsplash Recent state-of-the-art NLP pre-trained models also use a language model to learn contextualized text representation. …
Cross-lingual Language Model
Author(s): Edward Ma Originally published on Towards AI. Discussing XLMs and unsupervised cross-lingual word embedding by multilingual neural language models Photo by Edward Ma on Unsplash A pre-trained model is proven to improve the downstream problem. Lample and Conneau propose two new …
Attention Is All You Need — Transformer
Author(s): Sherwin Chen Originally published on Towards AI. Positional Encoding Top highlight from https://wall.alphacoders.com/big.php?i=845641 Recurrent Neural Networks(RNNs), Long Short-Term Memory(LSTM) and Gated Recurrent Units(GRU) in particular, have been firmly established as state-of-the-art approaches in sequence modeling and transduction problems. Such models typically …
Getting the data
Author(s): Avishek Nag Originally published on Towards AI. Comparative study of different vector space models & text classification techniques like XGBoost and others In this article, we will discuss different text classification techniques to solve the BBC new article categorization problem. We …
Introduction to the Architecture of Recurrent Neural Networks (RNNs)
Author(s): Manish Nayak Originally published on Towards AI. RNNs Architecture U+007C Towards AI Introduction In my previous post, I explain different ways of representing text as a vector. you can read about Word2Vec, Doc2Vec and you can also find a jupyter notebook …
Introduction
Author(s): Manish Nayak Originally published on Towards AI. Machine Learning An Intuitive Introduction of Word2Vec by Building a Word2Vec From Scratch Understanding Word2Vec, and it’s advantages In this article, I will try to explain Word2Vec vector representation, an unsupervised model that learns …
Step 4: Logistic regression
Author(s): Rashmi Margani Originally published on Towards AI. Blending NB And SVM U+007C Towards AI Naive Bayes(NB)-Support Vector Machine(SVM): Art Of State Result Hands-On Guide using Fast.ai SVM with NB feature: State of art performance model variance Before getting into Model variant …
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