nlp

Top 10 NLP Concepts Interview Questions and Answers Natural Language Processing (NLP) terms for data scientist and machine learning engineer interviews

Top 10 NLP Concepts Interview Questions and Answers

Natural Language Processing (NLP) terminologies are frequently asked during data science and machine learning interviews. In this tutorial, we will talk about the top 10 Natual Language Processing (NLP) concepts interview questions and how to answer them. The top 10 questions are: Resources for this post: Let’s get started! Question 1: What are vocabularies, documents, …

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Transfer Learning for Text Classification Using PyTorch Fine-tuning a pretrained transformer BERT model for customized sentiment analysis using PyTorch training loops

Transfer Learning for Text Classification Using PyTorch

Hugging Face provides three ways to fine-tune a pretrained text classification model: PyTorch, Tensorflow Keras, and transformer trainer. Compared with the other two ways, PyTorch training loops provide more customization and easier debugging of the training loops. This tutorial will use PyTorch to fine-tune a text classification model. We will talk about the following: If …

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Sentiment Analysis: Hugging Face Zero-shot Model vs Flair Pre-trained Model Which pre-trained Natual Language Processing (NLP) model has better prediction accuracy for the sentiment analysis, Hugging Face or Flair?

Sentiment Analysis: Hugging Face Zero-shot Model vs Flair Pre-trained Model

There are different methods for sentiment analysis. Some examples are lexicon-based methods, building customized models, using cloud services for sentiment predictions, or using pre-trained language models. In this tutorial, we will compare two state-of-art deep-learning pre-trained models for sentiment analysis, one from Hugging Face, and the other from Flair. We will talk about: Resources for …

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sentiment positive negative

TextBlob VS VADER For Sentiment Analysis Using Python

TextBlob and VADER are two of the most widely used sentiment analysis Python libraries. Comparing to machine learning approaches for sentiment analysis, TextBlob and VADER use a lexicon-based method. The lexicon approach has a mapping between words and sentiment, and the sentiment of a sentence is the aggregation of the sentiment of each term. Lexicon …

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Sentiment Analysis Without Modeling: TextBlob vs VADER vs Flair

Sentiment Analysis Without Modeling: TextBlob vs VADER vs Flair

Sentiment analysis can be done with or without building a machine learning model. This article will go over the Python implementation of TextBlob, VADER, and Flair for non-model sentiment analysis. After reading the article, you will learn Resources for this post: Step 1: Install And Import Python Libraries The first step is to install and …

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Topic Modeling by Group Using Deep Learning in Python Topics by category using the Python package BERTopic on Airbnb reviews

Topic Modeling by Group Using Deep Learning in Python

Building one general topic model is not enough in some cases, especially when there are different categories with various properties and characteristics. For example, a commercial bank may be interested in topic models built for different lines of products such as credit cards, checking accounts, or student loan. A hotel chain may be interested in …

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Time Series Topic Tracking for Airbnb Reviews Track topic change over time using the Python package BERTopic

Time Series Topic Tracking for Airbnb Reviews

Time series topic tracking can help us understand how the topics change over time for reviews or social media posts. In this tutorial, we will use Airbnb review data to illustrate the following: The Python package used for the topic model in this tutorial is BERTopic. For more details about using this package, please check …

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Hyperparameter Tuning for BERTopic Model in Python Hyperparameter optimization for Transformer-based NLP topic modeling using the Python package BERTopic

Hyperparameter Tuning for BERTopic Model in Python

Hyperparameter tuning is an important optimization step for building a good topic model. BERTopic is a topic modeling python library that combines transformer embeddings and clustering model algorithms to identify topics in NLP (Natual Language Processing). In this tutorial, we will talk about the following: Please check out my previous tutorial Topic Modeling with Deep …

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Hierarchical Topic Model for Airbnb Reviews Extracting topics and sub-topics hierarchical structure in Airbnb reviews using the Python package BERTopic

Hierarchical Topic Model for Airbnb Reviews

Hierarchical topic models are the models that utilize the semantic hierarchy to identify topics and sub-topics for a collection of text. In this tutorial, we will use Airbnb review data to illustrate the following: The Python package used for the hierarchical model in this tutorial is BERTopic. For more details about using this package, please …

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