A complete introduction to GPT-3 with Use Case examples

GPT – 3 is one of the most exciting and versatile language models, which is good at almost eve...

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Deep Unveiling of the BERT Model

In 2018, Google proposed an exceptional language representation model called “BERT” which stands...

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Word Embedding

Introduction Humans have the ability to understand words and derive meaning from them easily. In tod...

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Jaccard Similarity – Text Similarity Metric in NLP

Jaccard Similarity is also known as the Jaccard index and Intersection over Union. Jaccard Similarit...

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TensorFlow : Text Classification of Movie Reviews

Text classification is a famous problem in Natural Language Processing where need to understand the ...

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Text Preprocessing: Handle Emoji & Emoticon

Text pre-processing step is a very crucial stage when you work with Natural Language Processing (NLP...

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Text Preprocessing: Removal of Punctuations

Text cleaning or Text pre-processing is a mandatory step when we are working with text in Natural La...

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Develop the text Classifier with TensorFlow Hub

Tensorflow Hub is a package for reusable machine learning modules in Tensorflow. A module consists o...

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Tensorflow : BERT Fine-tuning with GPU

The shortage of training data is one of the biggest challenges in Natural Language Processing. Becau...

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Introduction to BERT

BERT stands for Bidirectional Encoder Representations from Transformers. BERT is NLP Framework which...

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NLTK – WordNet

A WordNet is a semantically-oriented dictionary of English with synonyms, antonyms, and brief defini...

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Word Tokenization with NLTK

Word tokenization is the process of split the text into words is called the token. Tokenization is a...

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Installation of NLTK

NLTK (Natural language Toolkit) is one of the leading Python package to work with Natural Language P...

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Introduction to Natural Language Processing (NLP)

Natural Language Processing (NLP) is one of the most famous domain in the field of Machine Learning ...

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Cosine Similarity – Text Similarity Metric

Text Similarity has to determine how the two text documents close to each other in terms of their co...

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Introduction to Word Embeddings

Word Embeddings are basically a type of word representation that allows words with similar meaning t...

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NLP – Stop Words

Stop words are the words which are very common in text documents such as a, an, the, you, your, etc....

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An Introduction to N-grams

An N-gram is a contiguous sequence of n items from a given sample of text or speech. In Natural Lan...

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Stemming and Lemmatization

Stemming and Lemmatization is the method to normalize the text documents. The main goal of the text ...

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TfidfVectorizer for text classification

The word count from text documents is very basic at the starting point. However simple word count is...

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CountVectorizer for text classification

As we are all aware that the machine can only understand the numbers not text. So it is necessary to...

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Regular Expression for Text Cleaning in NLP

Regular Expression is very useful for text manipulation in text cleaning phase of Natural Language P...

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Text Data Cleaning & Preprocessing

Text cleaning is one of the important part of natural language processing. The real-life human writa...

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Different Tokenization Technique for Text Processing

In this article, I have described the different tokenization method for text preprocessing. As all o...

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