Analytics Vidhya

JANUARY 17, 2022

The post Roadmap to Master NLP in 2022 appeared first on Analytics Vidhya. Introduction A few days ago, I came across a question on “Quora” that boiled down to: “How can I learn Natural Language Processing in just only four months?” ” Then I began to write a brief response.

NLP 400

NLP Natural Language Processing Data Science Neural Network 400

Unite.AI

OCTOBER 27, 2024

The ecosystem has rapidly evolved to support everything from large language models (LLMs) to neural networks, making it easier than ever for developers to integrate AI capabilities into their applications. is its intuitive approach to neural network training and implementation. environments. TensorFlow.js TensorFlow.js

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Neural Network Machine Learning NLP Natural Language Processing 162

Unite.AI

DECEMBER 7, 2024

These innovative platforms combine advanced AI and natural language processing (NLP) with practical features to help brands succeed in digital marketing, offering everything from real-time safety monitoring to sophisticated creator verification systems.

AI Tools 278

AI Tools Automation NLP Algorithm 278

Analytics Vidhya

MARCH 7, 2025

To this day, I remember coming across recurrent neural networks in our course work. I asked my advisor, “Should I use an LSTM or a GRU for this NLP project?” Sequence data excite you initially, but then confusion sets in when differentiating between the multiple architectures.

Neural Network 137

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Analytics Vidhya

JULY 22, 2022

He is a Data Scientist @Mckinsey & Company with over 5 years of experience, primarily working on NLP and related problems. The post The DataHour: Bias and Fairness in NLP appeared first on Analytics Vidhya.

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NLP Data Scientist Artificial Intelligence Artificial Intelligence 348

Unite.AI

NOVEMBER 8, 2023

Natural Language Processing (NLP) has experienced some of the most impactful breakthroughs in recent years, primarily due to the the transformer architecture. The introduction of word embeddings, most notably Word2Vec, was a pivotal moment in NLP. One-hot encoding is a prime example of this limitation. in 2017.

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BERT NLP Neural Network Natural Language Processing 298

Analytics Vidhya

MAY 17, 2024

Introduction In natural language processing (NLP), sequence-to-sequence (seq2seq) models have emerged as a powerful and versatile neural network architecture.

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Neural Network Natural Language Processing NLP 336

Unite.AI

MARCH 24, 2024

Bridging the Gap with Natural Language Processing Natural Language Processing (NLP) stands at the forefront of bridging the gap between human language and AI comprehension. NLP enables machines to understand, interpret, and respond to human language in a meaningful way.

Neural Network 354

Neural Network Robotics Natural Language Processing NLP 354

IBM Journey to AI blog

JULY 6, 2023

While artificial intelligence (AI), machine learning (ML), deep learning and neural networks are related technologies, the terms are often used interchangeably, which frequently leads to confusion about their differences. How do artificial intelligence, machine learning, deep learning and neural networks relate to each other?

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Analytics Vidhya

DECEMBER 13, 2021

This article was published as a part of the Data Science Blogathon Introduction In the past few years, Natural language processing has evolved a lot using deep neural networks. Many state-of-the-art models are built on deep neural networks. It […].

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BERT Neural Network Natural Language Processing Data Science 380

Analytics Vidhya

JULY 22, 2024

We’ll take you through a thorough examination of recent advancements in neural networks and algorithms, shedding light on the key ideas behind modern AI. Introduction In this article, we dive into the top 10 publications that have transformed artificial intelligence and machine learning.

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Marktechpost

JUNE 18, 2024

Two notable research papers contribute to this development: “Bayesian vs. PAC-Bayesian Deep Neural Network Ensembles” by University of Copenhagen researchers and “Deep Bayesian Active Learning for Preference Modeling in Large Language Models” by University of Oxford researchers.

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Unite.AI

JANUARY 18, 2025

While Central Processing Units (CPUs) and Graphics Processing Units (GPUs) have historically powered traditional computing tasks and graphics rendering, they were not originally designed to tackle the computational intensity of deep neural networks.

Generative AI 147

Generative AI Neural Network Robotics Natural Language Processing 147

Analytics Vidhya

SEPTEMBER 10, 2022

However, even though it’s easy to delve into the topic, many people are confused by the terminology and end up only implementing neural network […]. Introduction Deep learning is one of the hottest fields in the past decade, with applications in industry and research.

Neural Network 381

Neural Network Deep Learning Data Science NLP 381

Analytics Vidhya

MAY 29, 2023

A recurrent neural network is a class of artificial neural networks where connections between nodes can create a cycle, allowing output from some nodes to affect subsequent input to the same nodes.

Neural Network 304

Neural Network Natural Language Processing NLP 304

Towards AI

DECEMBER 21, 2024

This surprising connection between PCA and neural networks highlights how dimensionality reduction and representation learning are two sides of the same coin. This idea got me thinking: what if PCA concepts could make attention mechanisms in neural networks even better?

Neural Network 111

Neural Network Machine Learning NLP AI 111

Marktechpost

JANUARY 23, 2024

There are two major challenges in visual representation learning: the computational inefficiency of Vision Transformers (ViTs) and the limited capacity of Convolutional Neural Networks (CNNs) to capture global contextual information. A team of researchers at UCAS, in collaboration with Huawei Inc.

Convolutional Neural Networks 145

Convolutional Neural Networks Neural Network Computer Vision NLP 145

Towards AI

DECEMBER 12, 2024

We are diving into Mechanistic interpretability, an emerging area of research in AI focused on understanding the inner workings of neural networks. Jjj8405 is seeking an NLP/LLM expert to join the team for a project. DINN extends DWLR by adding feature interaction terms, creating a neural network architecture.

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Neural Network LLM Explainability NLP 105

Towards AI

DECEMBER 12, 2024

We are diving into Mechanistic interpretability, an emerging area of research in AI focused on understanding the inner workings of neural networks. Jjj8405 is seeking an NLP/LLM expert to join the team for a project. DINN extends DWLR by adding feature interaction terms, creating a neural network architecture.

Neural Network 104

Neural Network LLM Explainability NLP 104

Marktechpost

MAY 17, 2024

Natural language processing (NLP) has advanced significantly thanks to neural networks, with transformer models setting the standard. Although these models perform well on NLP tasks, they could be more practical in contexts with limited resources. These models have performed remarkably well across a range of criteria.

Neural Network 109

Neural Network NLP Natural Language Processing AI 109

Towards AI

DECEMBER 12, 2024

We are diving into Mechanistic interpretability, an emerging area of research in AI focused on understanding the inner workings of neural networks. Jjj8405 is seeking an NLP/LLM expert to join the team for a project. DINN extends DWLR by adding feature interaction terms, creating a neural network architecture.

Neural Network 103

Neural Network LLM Explainability NLP 103

Marktechpost

SEPTEMBER 17, 2024

In deep learning, neural network optimization has long been a crucial area of focus. Training large models like transformers and convolutional networks requires significant computational resources and time. One of the central challenges in this field is the extended time needed to train complex neural networks.

Neural Network 113

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 113

Unite.AI

NOVEMBER 5, 2024

The need for specialized AI accelerators has increased as AI applications like machine learning, deep learning , and neural networks evolve. The chip is designed for flexibility and scalability, enabling it to handle various AI workloads such as Natural Language Processing (NLP) , computer vision , and predictive analytics.

Deep Learning 189

Deep Learning AI AI Neural Network 189

Analytics Vidhya

DECEMBER 28, 2021

Prerequisites Working knowledge of Python and training neural networks using Tensorflow Introduction to BERT Model for Sentiment Analysis Sentiment Analysis is a major task in Natural […]. The post Fine-tune BERT Model for Sentiment Analysis in Google Colab appeared first on Analytics Vidhya.

BERT 328

BERT Neural Network Python Data Science 328

Unite.AI

MAY 29, 2024

This advancement has spurred the commercial use of generative AI in natural language processing (NLP) and computer vision, enabling automated and intelligent data extraction. Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text.

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Data Extraction Neural Network Large Language Models NLP 273

Towards AI

JANUARY 29, 2025

Generative AI is powered by advanced machine learning techniques, particularly deep learning and neural networks, such as Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs). Study neural networks, including CNNs, RNNs, and LSTMs. Why Become a Generative AI Engineer in 2025?

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AI Engineer Generative AI Neural Network BERT 98

Analytics Vidhya

JUNE 26, 2023

Introduction Attention models, also known as attention mechanisms, are input processing techniques used in neural networks. They allow the network to focus on different aspects of complex input individually until the entire data set is categorized.

Neural Network 305

Neural Network Categorization Deep Learning NLP 305

Analytics Vidhya

JUNE 5, 2023

These gargantuan neural networks have revolutionized how machines learn and generate human language, propelling the boundaries of what was once thought possible.

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Marktechpost

APRIL 6, 2024

Transformers have transformed the field of NLP over the last few years, with LLMs like OpenAI’s GPT series, BERT, and Claude Series, etc. Let’s delve into the role of transformers in NLP and elucidate the process of training LLMs using this innovative architecture. appeared first on MarkTechPost.

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Large Language Models NLP Convolutional Neural Networks Neural Network 122

Marktechpost

DECEMBER 19, 2023

Recurrent Neural Networks (RNNs) and Transformers are the most common methods; each has advantages and disadvantages. By comparing the suggested architecture to SoTA, the researchers find that it performs similarly while being more cost-effective across a range of natural language processing (NLP) workloads.

Neural Network 135

Neural Network Natural Language Processing Deep Learning Artificial Intelligence 135

Towards AI

JUNE 7, 2024

The idea is to give a quick high-level view of how recursive neural networks are trained for datasets that have a continuous internal structure, such as text. In standard neural networks, each layer only depends on the layer immediately above it, which means that a network forms a linear structure which “forgets” the previous data.

Neural Network 89

Neural Network Machine Learning NLP AI 89

Towards AI

JULY 20, 2023

The Lookout — “All’s Well” | Homer NATURAL LANGUAGE PROCESSING (NLP) WEEKLY NEWSLETTER The NLP Cypher | 03.07.21 Oh and by the way, Maybe… the universe is just a giant neural network… ?‍♂️ ‍♂️ The Universe Might Be One Big Neural Network, Study Finds One scientist says the universe is a giant neural net.

NLP 98

NLP Neural Network Natural Language Processing Machine Learning 98

Marktechpost

DECEMBER 16, 2023

Trained on a dataset from six UK hospitals, the system utilizes neural networks, X-Raydar and X-Raydar-NLP, for classifying common chest X-ray findings from images and their free-text reports. An NLP algorithm, X-Raydar-NLP, was trained on 23,230 manually annotated reports to extract labels.

Neural Network 96

Neural Network Auto-classification NLP Natural Language Processing 96

ODSC - Open Data Science

FEBRUARY 17, 2023

Natural language processing (NLP) has been growing in awareness over the last few years, and with the popularity of ChatGPT and GPT-3 in 2022, NLP is now on the top of peoples’ minds when it comes to AI. The chart below shows 20 in-demand skills that encompass both NLP fundamentals and broader data science expertise.

NLP 111

NLP Data Science Deep Learning BERT 111

Marek Rei

NOVEMBER 4, 2024

Proposes that this is not a skill that will develop from one task, and that it should be evaluated through the interpretation of neural networks (for example whether a specific neuron can be identified to detect the emotion of others). Nature Communications 2024.

Machine Learning 80

Machine Learning NLP Large Language Models LLM 80

Towards AI

FEBRUARY 3, 2025

DeepSeek AI is an advanced AI genomics platform that allows experts to solve complex problems using cutting-edge deep learning, neural networks, and natural language processing (NLP). What is DeepSeek AI? DeepSeek AI, on the other hand, isnt just another fancy AI gadget, its a revolutionary breakthrough.

Natural Language Processing 125

Natural Language Processing OpenAI Neural Network AI 125

Towards AI

NOVEMBER 8, 2024

Natural Language Processing, or NLP, used to be about just getting computers to follow basic commands. Text generation is said to be the branch of natural language processing (NLP) and it is primarily focused on creating coherent and contextually relevant texts automatically.

Automation 122

Automation Natural Language Processing Neural Network NLP 122