Category: NLP

Articles About Natural Language Processing

Advanced, Classification, Libraries, NLP, Python, Structured Data, Supervised, Technique, Text

Automate NLP Tasks using EvalML Library

“The quality of your communication shapes the quality of your life.”, with this beautiful line let’s s begin and understand what we will learn in this article. In my one of the article, I have explained how to automate machine learning problem statement using EvalML. In this article we will look at “is it possible to automate NLP task using EvalML?”. What is EvalML? It is an AutoML library that builds, optimizes, and evaluates machine learning pipelines using domain-specific objective […]

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NLP

Issue #128 – Using Context in Neural MT Training Objectives

29 Apr21 Issue #128 – Using Context in Neural MT Training Objectives Author: Dr. Danielle Saunders, Research Scientist @ RWS We have a guest post this week, but it’s not really a “guest” as the recently acquired SDL team joins forces with Iconic as part of RWS! Nevertheless, we are pleased to have Dr. Danielle Saunders describe her most recent paper on using context in Minimum Risk Training to improve machine translation tuning and to fix hallucinations. Enjoy! Introduction In […]

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Advanced, NLP, Project, Technique

Building a Conversational Bot using LUIS

Introduction Companies are increasingly inclining towards having chatbots for their businesses for multiple applications. Amongst the numerous API providers in the chatbot landscape that focus on Natural Language Programming (NLP) and Natural Language Understanding (NLU), I would be demonstrating how to build a chatbot that can automate the process of scheduling interviews using Microsoft’s LUIS. Scheduling interviews comes with a lot of challenges like finding out a suitable slot for everyone, including other participants, rescheduling an interview on a participant’s […]

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NLP

MLOps Primer – 2021

Machine learning operations (MLOps) is becoming an exciting space as we figure out the best practices and technologies to deploy machine learning models in the real world. MLOps enable ML teams to build responsible and scalable machine learning systems and infrastructure. This facilitates tasks that range from risk assessment to building and testing to monitoring. While still in its infancy, MLOps has attracted machine learning engineers and software engineers in general. With every new paradigm comes new challenges and opportunities […]

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Advanced, Data Exploration, Data Visualization, NLP, Project, Python, Technique, Text, Unsupervised

Speed Up Text Pre Processing Using TextHero Python Library

Introduction     Natural Language Processing, typically abbreviated as NLP, is a branch of artificial intelligence that manages the connection among PCs and people utilizing the regular language. A definitive target of NLP is to peruse, unravel, comprehend, and figure out the human dialects in a way that is significant. Most NLP strategies depend on AI to get significance from human dialects. NLP involves applying calculations to recognize and separate the characteristic language decides to such an extent that the […]

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Beginner, NLP, Python, Technique, Text, Unsupervised

A Simple Guide to Metrics for Calculating String Similarity

Introduction One of the applications of Natural Language Processing is auto-correction and spellings checks. All of us have encountered this that if we type an incorrect or typo in the Google search engine, then the engine automatically corrects it and suggests the right word in its place. How does the engine do that? How does it know what word we wanted to write or ask? That is what we will be covering in this article. The methods available to check […]

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Beginner, Deep Learning, NLP

Role of Machine Learning in Natural Language Processing

Introduction Machine Learning and Natural Language Processing are important subfields of Artificial Intelligence that have gained prominence in recent times. Machine Learning and Natural Language Processing play a very important part in making an artificial agent into an artificial ‘intelligent’ agent. An Artificially Intelligent system can accept better information from the environment and can act on the environment in a user-friendly manner because of the advancement in Natural Language Processing. Similarly, an Artificially Intelligent System can process the received information […]

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constrained parameter initialisation, NLP

Issue #127 – On the Sparsity of Neural MT Models

22 Apr21 Issue #127 – On the Sparsity of Neural MT Models Author: Dr. Jingyi Han, Machine Translation Scientist @ Iconic Introduction Looking at the evolution of Neural Machine Translation (NMT), from a simple feed-forward approach to the recent state of the art Transformer architecture, models are getting more and more complicated by involving a large number of parameters to fit a massive data well. As a consequence, over-parameterization is a common problem suffered by NMT models, and it is […]

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Advanced, NLP

How to Use Google’s NLP API to Analyze and Produce Better Content

Introduction Machine learning has revolutionized the way content marketers create content. It gave deep insights into what actually the search engine bots crawl and how they understand the natural language. Writing content today is a lot different than it was 15 years ago. In the past, the content was created for the Search Engines, which was enough to rank the website high. But, today, valuable content is not the one made specifically for search engines. In fact, creating such content […]

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NLP

MixKD: Towards Efficient Distillation of Large-Scale Language Models

March 17, 2021 By: Kevin J Liang, Weituo Hao, Dinghan Shen, Yufan Zhou, Weizhu Chen, Changyou Chen, Lawrence Carin Abstract Large-scale language models have recently demonstrated impressive empirical performance. Nevertheless, the improved results are attained at the price of bigger models, more power consumption, and slower inference, which hinder their applicability to low-resource (both memory and computation) platforms. Knowledge distillation (KD) has been demonstrated as an effective framework for compressing such big models. However, large-scale neural network systems are prone […]

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