Category: NLP

Articles About Natural Language Processing

Beginner, Machine Learning, NLP, Python, Technique Leave a comment

Machine Learning in Cyber Security — Malicious Software Installation

Introduction Monitoring of user activities performed by local administrators is always a challenge for SOC analysts and security professionals. Most of the security framework will recommend the implementation of a whitelist mechanism. However, the real world is often not ideal. You will always have different developers or users having local administrator rights to bypass controls specified. Is there a way to monitor the local administrator activities?

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Nearest Neighbor MT, NLP

Issue #102 – Nearest Neighbour Machine Translation

08 Oct20 Issue #102 – Nearest Neighbour Machine Translation Author: Dr. Patrik Lambert, Senior Machine Translation Scientist @ Iconic Introduction Taking into account context information in neural MT is an active area of research, with applications in document-level translation, domain adaptation and multilingual neural MT. Today we take a look at a method which combines predictions from a neural MT model and from a nearest neighbour classifier, retrieved from similar contexts in a datastore of cached examples. This approach, called […]

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NLP

A Simple Guide On Using BERT for Binary Text Classification.

Please consider using the Simple Transformers library as it is easy to use, feature-packed, and regularly updated. The article still stands as a reference to BERT models and is likely to be helpful with understanding how BERT works. However, Simple Transformers offers a lot more features, much more straightforward tuning options, all the while being quick and easy to use! The links below should help you get started quickly. Binary Classification

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Leveraging Monolingual Data, NLP

Issue #101 – Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation

02 Oct20 Issue #101 – Leveraging Monolingual Data with Self-Supervision for Multilingual Neural Machine Translation Author: Dr. Chao-Hong Liu, Machine Translation Scientist @ Iconic Introduction Multilingual Neural Machine Translation (NMT), which enables zero-shot MT, is a significant development since the start of NMT. On the one hand, we have evidence that models trained with multiple languages can outperform those trained on a bilingual basis. On the other hand, multilingual NMT also enables us to train models of a language pair […]

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Beginner, Data Science, Libraries, NLP, Programming, Python, Text, Unstructured Data Leave a comment

Beginners Tutorial for Regular Expressions in Python

Importance of Regular Expressions In last few years, there has been a dramatic shift in usage of general purpose programming languages for data science and machine learning. This was not always the case – a decade back this thought would have met a lot of skeptic eyes! This means that more people / organizations are using tools like Python / JavaScript for solving their data needs. This is where Regular Expressions become super useful. Regular expressions are normally the default way […]

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Classification, Data Science, Intermediate, NLP, Project, Python, Supervised, Technique, Text, Unstructured Data Leave a comment

Sentiment Analysis of Twitter Posts on Chennai Floods using Python

Introduction The best way to learn data science is to do data science. No second thought about it! One of the ways, I do this is continuously look for interesting work done by other community members. Once I understand the project, I do / improve the project on my own. Honestly, I can’t think of a better way to learn data science. As part of my search, I came across a study on sentiment analysis of Chennai Floods on Analytics Vidhya. […]

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Beginner, Libraries, NLP, Python, Text, Unstructured Data Leave a comment

How to Use Texthero to Prepare a Text-based Dataset for Your NLP Project

Introduction Natural Language Processing (NLP) is one of the most important fields of study and research in today’s world. It has many applications in the business sector such as chatbots, sentiment analysis, and document classification. Preprocessing and representing text is one of the trickiest and most annoying parts of working on an NLP project. Text-based datasets can be incredibly thorny and difficult to preprocess. But fortunately, the latest Python package called Texthero can help you solve these challenges. What is […]

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Advanced, NLP, Project, Python, Ranking, Technique, Text, Unstructured Data, Word Embeddings Leave a comment

Information Retrieval using word2vec based Vector Space Model

Overview Learn about Information Retrieval (IR), Vector Space Models (VSM), and Mean Average Precision (MAP) Create a project on Information Retrieval using word2vec based Vector Space Model   Introduction “Google it!”- Isn’t it something we say every day? Whenever we come across something that we don’t know about, we “Google it.” Google Search is a great tool that can be used for even finding a needle from a haystack. This generation absolutely relies on Google for answers to all kinds […]

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Algorithm, Deep Learning, Intermediate, NLP, Supervised, Text, Unstructured Data Leave a comment

A Simple Introduction to Sequence to Sequence Models

Overview In this article, I would give you an overview of sequence to sequence models which became quite popular for different tasks like machine translation, video captioning, image captioning, question answering, etc. Prerequisites: The reader should already be familiar with neural networks and, in particular, recurrent neural networks (RNNs). In addition, knowledge of LSTM or GRU models is preferable. If you are not familiar with LSTM I would prefer you to read LSTM- Long Short-Term Memory.

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NLP

How to develop LSTM recurrent neural network models for text classification problems in Python using Keras deep learning library

How to develop LSTM recurrent neural network models for text classification problems in Python using Keras deep learning library Automatic text classification or document classification can be done in many different ways in machine learning as we have seen before. This article aims to provide an example of how a Recurrent Neural Network (RNN) using the

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