Natural Language Processing (NLP) Interview questions on NLP Natural language processing may be used to query the data using voice or text in natural language.
Machine Learning (ML) Understanding Bleu Score BLEU (Bilingual Evaluation Understudy) score was proposed in 2002 and has quickly become the standard score for evaluating machine translation output. It measures the similarity between a machine's translated text and a set of good quality human reference translations.
Natural Language Processing (NLP) Retrieval Augmented Generation (RAG): Basics In this article at OpenGenus, we have explored a new finetuning technique for Large Language Models (LLMs) developed by Meta (formerly Facebook). This technique is known as Retrieval Augmented Generation (RAG).
Deep Learning 7 Different Prompting Techniques In this article at OpenGenus, we will explore various techniques utilized in prompt engineering, shedding light on the most popular and effective approaches.
Natural Language Processing (NLP) Linguistic Data Mining and Corpus Linguistics Linguistic Data Mining and Corpus Linguistics are two interrelated fields of computational linguistics that have gained significant attention in recent years. The article provides an overview of the key concepts and methods used in both, pros and cons and future prospects.
Natural Language Processing (NLP) Key Terms/ Topics in Natural Language Processing (NLP) In this article at OpenGenus, we will explore some of the fundamental terms used in NLP and their brief descriptions.
Deep Learning Building your own GPT code assistant In this article, we have explored how one can build their own GPT code assistant that is Code generation using GPT model architecture.
Natural Language Processing (NLP) Lexicon in NLP In this article at OpenGenus, we will dive into the concept of lexicon in NLP, explore its importance, implementation, applications, and its role in various NLP tasks.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
Natural Language Processing (NLP) Paraphrasing in NLP For this article, our aim would be to analyze different paraphrasing algorithms and their implementation in Python.
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.
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.
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.
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.
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.
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.