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Top 10 blogs on NLP in Analytics Vidhya 2022

Analytics Vidhya

Introduction Natural language processing (NLP) is a field of computer science and artificial intelligence that focuses on the interaction between computers and human (natural) languages. Natural language processing (NLP) is […].

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Hugging Face Transformers Pipeline Functions | Advanced NLP

Analytics Vidhya

Objective This blog post will learn how to use the Hugging face transformers functions to perform prolonged Natural Language Processing tasks. This article was published as a part of the Data Science Blogathon.

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Transformer Models: The future of Natural Language Processing

Data Science Dojo

Transformer models are a type of deep learning model that are used for natural language processing (NLP) tasks. They are able to learn long-range dependencies between words in a sentence, which makes them very powerful for tasks such as machine translation, text summarization, and question answering.

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Transformer Models: The future of Natural Language Processing

Data Science Dojo

Transformer models are a type of deep learning model that are used for natural language processing (NLP) tasks. They are able to learn long-range dependencies between words in a sentence, which makes them very powerful for tasks such as machine translation, text summarization, and question answering.

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Knowledge graphs and LLMs: An integration to transform natural language processing

Data Science Dojo

Combining knowledge graphs (KGs) and LLMs produces a system that has access to a vast network of factual information and can understand complex language. This blog aims to explore the potential of integrating knowledge graphs and LLMs, navigating through the promise of revolutionizing AI. What are large language models (LLMs)?

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Top 10 Deep Learning Projects for Beginners

Pickl AI

Summary: This article presents 10 engaging Deep Learning projects for beginners, covering areas like image classification, emotion recognition, and audio processing. Each project is designed to provide practical experience and enhance understanding of key concepts in Deep Learning. What is Deep Learning?

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Understanding Autoencoders in Deep Learning

Pickl AI

Summary: Autoencoders are powerful neural networks used for deep learning. Their applications include dimensionality reduction, feature learning, noise reduction, and generative modelling. In this blog, we will explore what autoencoders are, how they work, their various types, and real-world applications. Let’s dive in!