Transfer learning is explained, and the advantages and disadvantages are summed up. Types of transfer learning in NLP are summed up, and a list of the top models commonly used for transfer learning...
The Natural Language Processing (NLP) Blog
Topic: Natural Language Processing
MinHash — How To Deal With Finding Similarity At Scale With Python Code To Get Started
What is MinHash? MinHash is a technique for estimating the similarity between two sets. It was first introduced in information retrieval to evaluate the similarity between documents quickly. The...
SimHash — The Ultimate Guide And How To Get Started Guide In Python
What is SimHash? Simhash is a technique for generating a fixed-length "fingerprint" or "hash" of a variable-length input, such as a document or a piece of text. It is similar to a hash function and...
![How To Implement Fuzzy String Matching [4 Ways In Python]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2023/01/fuzzy-logic-hot-cold.jpg?fit=1024%2C1024&ssl=1)
How To Implement Fuzzy String Matching [4 Ways In Python]
This article discusses one of the most valuable tools when analysing textual data in natural language processing — fuzzy string matching. We first discuss what it is, its typical applications and...
![How To Implement Abstractive Text Summarization In Python [2 Ways]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2022/12/summarization.jpg?fit=1024%2C576&ssl=1)
How To Implement Abstractive Text Summarization In Python [2 Ways]
Abstractive text summarization is a valuable tool in Python when working with large documents, or you quickly want to summarize data. In this article, we discuss applications of abstractive text...
Top 15 Most Popular Machine Learning And Deep Learning Algorithms For NLP
This list covers the top 7 machine learning algorithms and 8 deep learning algorithms used for NLP. If you are new to using machine learning algorithms for NLP, we suggest starting with the first...
Reinforcement Learning In NLP Made Simple & 5 Relevant Tools To Get Started
This article covers reinforcement learning and its application in natural language processing (NLP). It also covered the latest developments in the field, a discussion on whether you should start...
Top 14 Steps To Build A Complete NLTK Preprocessing Pipeline In Python
This is a complete guide on utilising NLTK to build a whole preprocessing pipeline. Take the time to read through the different components so you know how to start building your pipeline. What is an...
![How To Implement Bag-Of-Words In Python [2 Ways: scikit-learn & NLTK]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2022/12/bag-of-words.jpg?fit=960%2C540&ssl=1)
How To Implement Bag-Of-Words In Python [2 Ways: scikit-learn & NLTK]
In this guide, we cover how to start with the bag-of-words technique in Python. We first cover what a bag-of-words approach is and provide an example. We then cover the advantages and disadvantages...
![Text Classification: How To In Python [Best 2 Ways Machine Learning & Deep Learning]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2022/12/random-forest.jpg?fit=960%2C540&ssl=1)
Text Classification: How To In Python [Best 2 Ways Machine Learning & Deep Learning]
Text classification is an important natural language processing (NLP) technique that allows us to turn unstructured data into structured data; many different algorithms allow you to do this, and so...
Top 7 Ways To Implement Document & Text Similarity In Python: NLTK, Scikit-learn, BERT, RoBERTa, FastText and PyTorch
Text similarity is a really useful natural language processing (NLP) tool. It allows you to find similar pieces of text and has many real-world use cases. This article discusses text similarity, its...
Text Generation NLP – Everything You Need To Know / Python Code To Get Started
What is text generation in NLP? Text generation is a subfield of natural language processing (NLP) that deals with generating text automatically. It has a wide range of applications, including...
![How To Translate Text In Python [Best 2 Ways APIs & Libraries]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2022/12/translate-python.jpg?fit=1024%2C576&ssl=1)
How To Translate Text In Python [Best 2 Ways APIs & Libraries]
This guide covers how to translate text in Python. Machine translation is a prominent natural language processing (NLP) application that is not very straightforward. We start by covering what is...
Sentence Embedding More Powerful Than Word Embedding? What Is The Difference
What is sentence embedding? Sentence embedding is a technique for representing a natural language sentence as a fixed-length numerical vector. The goal is to encode the semantic meaning and content...
![How To Implement Sentiment Analysis In Python [Best 5 Tools: TextBlob, Vader, NLTK, BERT, SpaCy]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2022/12/sentiment.jpg?fit=1024%2C576&ssl=1)
How To Implement Sentiment Analysis In Python [Best 5 Tools: TextBlob, Vader, NLTK, BERT, SpaCy]
Several powerful libraries and frameworks in Python can be used for sentiment analysis. These libraries will be covered below. The code examples of using the various libraries will be covered at the...
How To Get Started With Topic Modelling In Python— ML And Deep Learning Algorithms
What is topic modelling? Topic modelling is a technique used in natural language processing (NLP) to automatically identify and group similar words or phrases in a text. This lets us figure out the...
Top 3 Ways To Implement Stemming In Python With Advantages, Disadvantages, Different Algorithms & Alternatives
What is stemming? Stemming is the process of reducing a word to its base or root form. For example, the stem of the word "running" is "run," and the stem of the word "swimming" is "swim." Stemming...
![How To Implement Keyword Extraction [3 Ways In Python With NLTK, SpaCy & BERT]](https://i0.wp.com/spotintelligence.com/wp-content/uploads/2022/12/POS-tagging.jpg?fit=960%2C540&ssl=1)
How To Implement Keyword Extraction [3 Ways In Python With NLTK, SpaCy & BERT]
What is Keyword extraction? Keyword extraction is figuring out which words and phrases in a piece of text are the most important. These keywords can be used to summarise the content of the text. A...
