Analytics Vidhya

AUGUST 9, 2022

Introduction to Minerva [link] Google presented Minerva; a neural network created in-house that can break calculation questions and take on other delicate areas like quantitative reasoning. The model for natural language processing is called Minerva.

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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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Analytics Vidhya

FEBRUARY 3, 2023

For example, researchers predicted that deep neural networks would eventually be used for autonomous image recognition and natural language processing as early as the 1980s. As a result, numerous researchers have focused on creating intelligent machines throughout history.

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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.

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Analytics Vidhya

JULY 20, 2020

Introduction With the advancement in deep learning, neural network architectures like recurrent neural networks (RNN and LSTM) and convolutional neural networks (CNN) have shown. The post Transfer Learning for NLP: Fine-Tuning BERT for Text Classification appeared first on Analytics Vidhya.

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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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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.

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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.

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Unite.AI

AUGUST 19, 2024

Neural networks have been at the forefront of AI advancements, enabling everything from natural language processing and computer vision to strategic gameplay, healthcare, coding, art and even self-driving cars.

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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.

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Marktechpost

APRIL 5, 2024

King’s College London researchers have highlighted the importance of developing a theoretical understanding of why transformer architectures, such as those used in models like ChatGPT, have succeeded in natural language processing tasks. Check out the Paper. Also, don’t forget to follow us on Twitter.

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Marktechpost

OCTOBER 28, 2024

By inputting different prompts, users can observe the model’s ability to generate human-quality text, translate languages, write various kinds of creative content, and answer your questions in an informative way. This platform provides a valuable opportunity to understand the potential of AI in natural language processing.

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Towards AI

FEBRUARY 1, 2024

Many of us have a functional understanding of neural networks and how they work. In this article, I’ll implement a neural network from scratch, going over different concepts like derivatives, gradient descent, and backward propagation of gradients. def f(x): return 5*x - 9xs = np.arange(-5,5,0.25)ys

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Marktechpost

DECEMBER 10, 2024

Artificial Neural Networks (ANNs) have become one of the most transformative technologies in the field of artificial intelligence (AI). Artificial Neural Networks are computational systems inspired by the human brain’s structure and functionality. How Do Artificial Neural Networks Work?

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Analytics Vidhya

JANUARY 17, 2022

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?” This article was published as a part of the Data Science Blogathon. ” Then I began to write a brief response.

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Marktechpost

MAY 14, 2024

This article lists the top Deep Learning and Neural Networks books to help individuals gain proficiency in this vital field and contribute to its ongoing advancements and applications. Neural Networks and Deep Learning The book explores both classical and modern deep learning models, focusing on their theory and algorithms.

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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. NVIDIA has been the dominant player in this domain for years, with its powerful Graphics Processing Units (GPUs) becoming the standard for AI computing worldwide.

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Marktechpost

MAY 13, 2024

Vision Transformers (ViT) and Convolutional Neural Networks (CNN) have emerged as key players in image processing in the competitive landscape of machine learning technologies. The Rise of Vision Transformers (ViTs) Vision Transformers represent a revolutionary shift in how machines process images.

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Towards AI

NOVEMBER 8, 2024

Automating Words: How GRUs Power the Future of Text Generation Isn’t it incredible how far language technology has come? Natural Language Processing, or NLP, used to be about just getting computers to follow basic commands. Author(s): Tejashree_Ganesan Originally published on Towards AI.

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AI Weekly

JULY 27, 2023

techcrunch.com The Essential Artificial Intelligence Glossary for Marketers (90+ Terms) BERT - Bidirectional Encoder Representations from Transformers (BERT) is Google’s deep learning model designed explicitly for natural language processing tasks like answering questions, analyzing sentiment, and translation.

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Marktechpost

NOVEMBER 7, 2023

Neural networks have become indispensable tools in various fields, demonstrating exceptional capabilities in image recognition, natural language processing, and predictive analytics. The sum of these vectors is then passed to the next layer, creating a sparse and discrete bottleneck within the network.

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AI Weekly

AUGUST 10, 2023

Powered by clkmg.com In the News Deepset nabs $30M to speed up natural language processing projects Deepset GmbH today announced that it has raised $30 million to enhance its open-source Haystack framework, which helps developers build natural language processing applications.

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Marktechpost

JANUARY 24, 2024

With the growth of Deep learning, it is used in many fields, including data mining and natural language processing. However, deep neural networks are inaccurate and can produce unreliable outcomes. It can improve deep neural networks’ reliability in inverse imaging issues.

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Marktechpost

JANUARY 20, 2025

The automation of radiology report generation has become one of the significant areas of focus in biomedical natural language processing. The traditional approach to the automation of radiology reporting is based on convolutional neural networks (CNNs) or visual transformers to extract features from images.

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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. Researchers have been exploring advanced optimization techniques to make this process more efficient.

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Marktechpost

DECEMBER 19, 2023

Natural language processing, conversational AI, time series analysis, and indirect sequential formats (such as pictures and graphs) are common examples of the complicated sequential data processing jobs involved in these.

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Marktechpost

DECEMBER 23, 2023

Deep Neural Networks (DNNs) represent a powerful subset of artificial neural networks (ANNs) designed to model complex patterns and correlations within data. These sophisticated networks consist of multiple layers of interconnected nodes, enabling them to learn intricate hierarchical representations.

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Marktechpost

MAY 17, 2024

Natural language processing (NLP) has advanced significantly thanks to neural networks, with transformer models setting the standard. These models have performed remarkably well across a range of criteria. If you like our work, you will love our newsletter.

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Unite.AI

MARCH 2, 2025

From early neural networks to todays advanced architectures like GPT-4 , LLaMA , and other Large Language Models (LLMs) , AI is transforming our interaction with technology. These models can process vast amounts of data, generate human-like text, assist in decision-making, and enhance automation across industries.

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Unite.AI

SEPTEMBER 15, 2024

Their findings, recently published in Nature , represent a significant leap forward in the field of neuromorphic computing – a branch of computer science that aims to mimic the structure and function of biological neural networks.

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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). Lets begin! What is DeepSeek AI?

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AI Weekly

JULY 13, 2023

plos.org Screening for Chagas disease from the electrocardiogram using a deep neural network Worldwide, it is estimated that over 6 million people are infected with Chagas disease (ChD). We explore the use of deep neural networks to detect ChD from electrocardiograms (ECGs) to aid in the early detection of the disease.

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Marktechpost

OCTOBER 7, 2024

Recurrent neural networks (RNNs) have been foundational in machine learning for addressing various sequence-based problems, including time series forecasting and natural language processing. Let’s collaborate!

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Unite.AI

NOVEMBER 6, 2023

Neural Network: Moving from Machine Learning to Deep Learning & Beyond Neural network (NN) models are far more complicated than traditional Machine Learning models. Advances in neural network techniques have formed the basis for transitioning from machine learning to deep learning.

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Unite.AI

SEPTEMBER 18, 2024

The field of artificial intelligence is evolving at a breathtaking pace, with large language models (LLMs) leading the charge in natural language processing and understanding. This family of LLMs offers enhanced performance across a wide range of tasks, from natural language processing to complex problem-solving.

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AssemblyAI

MAY 3, 2023

The core process is a general technique known as self-supervised learning , a learning paradigm that leverages the inherent structure of the data itself to generate labels for training. This concept is not exclusive to natural language processing, and has also been employed in other domains.

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Unite.AI

MARCH 11, 2024

For example, a CAS designed for medical diagnostics might incorporate a component that excels in analyzing medical images, such as MRI or CT scans, alongside another component specialized in natural language processing to interpret patient histories and notes.

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