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Natural Language Processing (NLP)

Natural Language Processing (NLP) is the field of statistical analysis over textual data which involves tasks such as text summarization, topic modeling and much more.

Deep Learning

Megatron NLG model

NVIDIA created the massive transformer-based NLG model known as Megatron. It is based on the transformer architecture and made to produce text that resembles human speech quickly and accurately.

RAHUL ARORA
Deep Learning

Different types of Attention Mechanism

This article at OpenGenus aims to explore and walk you through the main types of Attention Mechanism models and the main approaches to Attention.

Ielin Daisy Ielin Daisy
Deep Learning

25 Must-Read NLP Papers in Deep Learning: A Comprehensive List

In this article at OpenGenus, we will list some of the must-read research papers in the field of NLP that have had a significant impact on the development of deep learning models for NLP tasks.

Akshat Sunil Pande
Research Papers

Attention Is All You Need: Paper Summary and Insights

In 2017, Vaswani et al. published a groundbreaking paper titled "Attention Is All You Need" at the Neural Information Processing Systems (NeurIPS) conference. This article at OpenGenus summarizes this paper and present the key insights.

Akshat Sunil Pande
Deep Learning

GPT-2 vs GPT-3 vs GPT-3.5 vs GPT-4: A Comprehensive Comparison of OpenAI LLMs

In this article at OpenGenus, we will provide a comprehensive comparison of the GPT models, highlighting the differences between GPT-2, GPT-3, GPT-3.5, and what we know so far about GPT-4.

Akshat Sunil Pande
Deep Learning

ERNIE 3.0 TITAN LLM

Pre-trained language models such as ERNIE, GPT, BERT have revolutionized the field of Natural Language Processing (NLP) by improving language generation, analysis and understanding. This article aims to provide you an overview of Baidu's ERNIE 3.0 TITAN LLM and briefly explore its architecture.

Ielin Daisy Ielin Daisy
Deep Learning

GPT-3 vs GPT-4

This article at OpenGenus aims to inculcate a basic technical understanding of the differences between GPT-3 and GPT-4.

Ambarish Deb Ambarish Deb
Deep Learning

Large Language Models (LLM)

This article at OpenGenus will explore the history of large language models (LLM), their underlying concepts, use cases, and real life implementations.

Ambarish Deb Ambarish Deb
Natural Language Processing (NLP)

Different Techniques for Sentence Semantic Similarity in NLP

Sentence Semantic similarity is a crucial task in natural language processing (NLP) that involves determining how similar two sentences or phrases are in meaning. There are different types of semantic similarity measures that can be used in NLP.

Nithish Singh Nithish Singh
Natural Language Processing (NLP)

Different techniques for Document Similarity in NLP

In Natural Language Processing (NLP), Document Similarity Calculation is a crucial task that involves checking how similar two or more documents are. This article shall focus on its use cases, the concept behind different techniques of document similarity, and their implementations in Python.

Ambarish Deb Ambarish Deb
Natural Language Processing (NLP)

Paraphrasing in NLP

For this article, our aim would be to analyze different paraphrasing algorithms and their implementation in Python.

Ambarish Deb Ambarish Deb
Natural Language Processing (NLP)

Chunking and Chinking in NLP

One important aspect of NLP is chunking, which involves the extraction of meaningful phrases or chunks from text data. Chinking is a related technique that involves the exclusion of certain words or phrases from a chunk.

Nithish Singh Nithish Singh
Natural Language Processing (NLP)

Polarity and Subjectivity in NLP

Polarity and subjectivity are two important concepts in natural language processing (NLP) that help machines understand the sentiment and emotions conveyed in human language. In this article, we'll explore these two concepts in depth and how they are used in NLP.

Nithish Singh Nithish Singh
Natural Language Processing (NLP)

Kneser-Ney Smoothing / Absolute discounting

In this article, we will discuss the process of Kneser-Ney Smoothing and Absolute Discounting, its implementation, pros and cons, use cases, and real-time applications etc.

Nithish Singh Nithish Singh
Natural Language Processing (NLP)

Sentiment analysis with NLP

Sentiment Analysis is the method of locating and extracting subjective information from text data. It entails determining whether the emotional bias of a text is positive, negative, or neutral by looking at its contents.

Ambarish Deb Ambarish Deb
Deep Learning

DetectGPT Model: Detect text generated by GPT3

In this article, we'll be discussing DetectGPT, a natural language processing model that's been developed to detect whether a given text was generated by machine or written by a human.

Abhijeet Saroha Abhijeet Saroha
Natural Language Processing (NLP)

Stemming in NLP

The aim of this article would be to elaborate upon the third example i.e. Stemming - the concept behind it, it's use cases, suitability and implementation in Python and to provide a basic idea of said topic to the readers.

Ambarish Deb Ambarish Deb
Natural Language Processing (NLP)

Tokenization in NLP [Complete Guide]

In this article, we will look at the different approaches to tokenization and their pros and cons in Natural Language Processing (NLP).

Nithish Singh Nithish Singh
Natural Language Processing (NLP)

N-gram language model in NLP

In this article, we will explore what N-gram models are, how they work, their advantages and disadvantages, and finally, we'll provide an example of how to implement an N-gram model.

Nithish Singh Nithish Singh
Natural Language Processing (NLP)

Lemmatization in NLP

In this article, we have explored about Lemmatization approaches in NLP in depth and presented Lemmatization approaches in Python with code examples.

Nithish Singh Nithish Singh
Natural Language Processing (NLP)

Bag of Words (BoW) in NLP

The Bag of Words technique falls under the category of text representation in NLP, wherein the words are converted to numerical values which can be understood and used by algorithms.

Ambarish Deb Ambarish Deb
Natural Language Processing (NLP)

CBOW and Skip gram

This article at OpenGenus gives the idea of CBOW (Continuous Bag of Words) and Skip-gram in a detailed way along with differences between the two concepts.

Md. Reyanus Salehin
Natural Language Processing (NLP)

Stop Words in NLP

In this article, we shall focus on the concept of stopwords and implementation of stopword removal in NLP.

Ambarish Deb Ambarish Deb
Natural Language Processing (NLP)

POS Tagging in NLP using Python

POS tagging is a text preprocessing task within the ambit of Natural Language Processing (NLP) whose goal is to analyze the syntactic structure of a given sentence and to understand the input text in a better manner.

Ambarish Deb Ambarish Deb
Natural Language Processing (NLP)

40 Cutting-Edge NLP Project Ideas with source code

In this article, we have explored 40 Cutting-Edge NLP Project Ideas with source code and associated research papers. These projects form a strong part of a Machine Learning Engineer Portfolio.

Anay Dongre
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