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

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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Unite.AI

FEBRUARY 7, 2024

Machine learning (ML) is a powerful technology that can solve complex problems and deliver customer value. This is why Machine Learning Operations (MLOps) has emerged as a paradigm to offer scalable and measurable values to Artificial Intelligence (AI) driven businesses.

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Marktechpost

MAY 10, 2024

Machine learning is widely applied in finance for tasks like credit scoring, fraud detection, and trading. This course recommends top machine learning courses for finance professionals aiming to harness these techniques for better decision-making and performance.

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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

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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Marktechpost

MARCH 30, 2024

In 2024, the landscape of Python libraries for machine learning and deep learning continues to evolve, integrating more advanced features and offering more efficient and easier ways to build, train, and deploy models. PyTorch PyTorch is a widely used open-source machine learning library based on the Torch library.

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Mlearning.ai

MAY 30, 2023

Recurrent Neural Networks (RNNs) have become a potent tool for analysing sequential data in the large subject of artificial intelligence and machine learning. As we know that Convolutional Neural Network (CNN) is used for structured arrays of data such as image data. RNN is used for sequential data.

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Heartbeat

FEBRUARY 8, 2023

Source: Author The field of natural language processing (NLP), which studies how computer science and human communication interact, is rapidly growing. By enabling robots to comprehend, interpret, and produce natural language, NLP opens up a world of research and application possibilities.

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Marktechpost

DECEMBER 19, 2023

Advancements in deep learning have influenced a wide variety of scientific and industrial applications in artificial intelligence. Recurrent Neural Networks (RNNs) and Transformers are the most common methods; each has advantages and disadvantages.

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Analytics Vidhya

FEBRUARY 3, 2023

As a result, numerous researchers have focused on creating intelligent machines throughout history. 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.

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Mlearning.ai

JANUARY 26, 2023

Introduction Natural language processing (NLP) sentiment analysis is a powerful tool for understanding people’s opinions and feelings toward specific topics. NLP sentiment analysis uses natural language processing (NLP) to identify, extract, and analyze sentiment from text data.

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Dlabs.ai

DECEMBER 9, 2021

Natural language processing (NLP) is a core part of artificial intelligence. Natural Language Processing Succinctly Author : Joseph D. Booth The first book in our list focuses on machine learning-based NLP. There’s plenty of literature that covers the topic.

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Marktechpost

MARCH 4, 2024

Artificial Intelligence (AI) and Deep Learning, with a focus on Natural Language Processing (NLP), have seen substantial changes in the last few years. RNN’s innate ability to process sequential data makes them well-suited for tasks involving sequences, such as time-series data, text, and speech.

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ODSC - Open Data Science

JUNE 9, 2023

The 1970s introduced bell bottoms, case grammars, semantic networks, and conceptual dependency theory. In the 90’s we got grunge, statistical models, recurrent neural networks and long short-term memory models (LSTM). It uses a neural network to learn the vector representations of words from a large corpus of text.

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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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Heartbeat

AUGUST 21, 2023

In this guide, we’ll talk about Convolutional Neural Networks, how to train a CNN, what applications CNNs can be used for, and best practices for using CNNs. What Are Convolutional Neural Networks CNN? CNNs are artificial neural networks built to handle data having a grid-like architecture, such as photos or movies.

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Heartbeat

SEPTEMBER 20, 2023

Pixabay: by Activedia Image captioning combines natural language processing and computer vision to generate image textual descriptions automatically. These algorithms can learn and extract intricate features from input images by using convolutional layers.

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IBM Journey to AI blog

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is machine learning? This post will dive deeper into the nuances of each field.

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IBM Journey to AI blog

OCTOBER 16, 2023

Machine learning (ML)—the artificial intelligence (AI) subfield in which machines learn from datasets and past experiences by recognizing patterns and generating predictions—is a $21 billion global industry projected to become a $209 billion industry by 2029.

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AI Weekly

OCTOBER 26, 2023

cryptopolitan.com Applied use cases Alluxio rolls out new filesystem built for deep learning Alluxio Enterprise AI is aimed at data-intensive deep learning applications such as generative AI, computer vision, natural language processing, large language models and high-performance data analytics. voxeurop.eu

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Towards AI

JUNE 27, 2023

Last Updated on June 27, 2023 by Editorial Team Source: Unsplash This piece dives into the top machine learning developer tools being used by developers — start building! In the rapidly expanding field of artificial intelligence (AI), machine learning tools play an instrumental role.

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Towards AI

FEBRUARY 20, 2024

Beginner’s Guide to ML-001: Introducing the Wonderful World of Machine Learning: An Introduction Everyone is using mobile or web applications which are based on one or other machine learning algorithms. You might be using machine learning algorithms from everything you see on OTT or everything you shop online.

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AI News

DECEMBER 18, 2023

Zheng first explained how over a decade working in digital marketing and e-commerce sparked her interest more recently in data analytics and artificial intelligence as machine learning has become hugely popular. “There’s a lot of misconceptions, definitely.

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Towards AI

APRIL 27, 2023

Understanding the Principles, Challenges, and Applications of Gradient Descent Image by Author with @MidJourney Introduction to Gradient Descent Gradient descent is a fundamental optimization algorithm used in machine learning and data science to find the optimal values of the parameters in a model.

Machine Learning 85

Machine Learning Neural Network Convolutional Neural Networks Natural Language Processing 85

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

JANUARY 15, 2024

Transformers have taken over from recurrent neural networks (RNNs) as the preferred architecture for natural language processing (NLP). Transformers stand out conceptually because they directly access each token in a sequence, unlike RNNs that rely on maintaining a recurring state of past inputs.

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Heartbeat

OCTOBER 11, 2023

This process is known as machine learning or deep learning. Two of the most well-known subfields of AI are machine learning and deep learning. What is Machine Learning? Machine learning algorithms can make predictions or classifications based on input data.

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Heartbeat

MARCH 22, 2023

Learn NLP data processing operations with NLTK, visualize data with Kangas , build a spam classifier, and track it with Comet Machine Learning Platform Photo by Stephen Phillips — Hostreviews.co.uk These applications also leverage the power of Machine Learning and Deep Learning. """

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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. The dataset, spanning 13 years, included 2,513,546 chest x-ray studies and 1,940,508 usable free-text radiological reports.

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Pickl AI

AUGUST 3, 2023

Introduction to Deep Learning Algorithms: Deep learning algorithms are a subset of machine learning techniques that are designed to automatically learn and represent data in multiple layers of abstraction. The initial weights and biases of the neural network are randomly assigned.

Deep Learning 52

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Mlearning.ai

APRIL 21, 2023

Natural Language Processing Transformers, the neural network architecture, that has taken the world of natural language processing (NLP) by storm, is a class of models that can be used for both language and image processing. Not this Transformers!! ?

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Marktechpost

JULY 12, 2023

Artificial neural networks have advanced significantly over the past few decades, propelled by the notion that more network complexity results in better performance. Modern technology has amazing processing capacity, enabling neural networks to perform these jobs excellently and efficiently.

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Marktechpost

FEBRUARY 28, 2024

New standards are being set across various activities by Large Language Models (LLMs), which are causing a revolution in natural language processing. Impractical computing complexity for extending contextual processing is caused by these techniques, which scale poorly with large text sequences.

Machine Learning 86

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NVIDIA Developer

JUNE 2, 2021

Applications for natural language processing (NLP) have exploded in the past decade. With the proliferation of AI assistants and organizations infusing their businesses with more interactive human-machine experiences, understanding how NLP techniques can be used to manipulate, analyze, and generate text-based data is essential.

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AI Weekly

JULY 13, 2023

psychologytoday.com Decoding How Spotify Recommends Music to Users Machine learning (ML) and artificial intelligence (AI) have revolutionized the music streaming industry by enhancing the user experience, improving content discovery, and enabling personalized recommendations. [Try Pluto for free today] pluto.fi AlphaGO was.

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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. 1.41%) (BRK.B

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