Marktechpost

OCTOBER 4, 2024

Evaluated Models Ready Tensor’s benchmarking study categorized the 25 evaluated models into three main types: Machine Learning (ML) models, Neural Network models, and a special category called the Distance Profile model. Prominent models include Long-Short-Term Memory (LSTM) and Convolutional Neural Networks (CNN).

Neural Network 105

Neural Network Machine Learning Convolutional Neural Networks Categorization 105

Becoming Human

MARCH 16, 2023

This post includes the fundamentals of graphs, combining graphs and deep learning, and an overview of Graph Neural Networks and their applications. Through the next series of this post here , I will try to make an implementation of Graph Convolutional Neural Network. How do Graph Neural Networks work?

Neural Network 87

Neural Network Auto-classification Convolutional Neural Networks Auto-complete 87

Unite.AI

MAY 29, 2024

Named Entity Recognition ( NER) Named entity recognition (NER), an NLP technique, identifies and categorizes key information in text. This architecture, leveraging neural networks like RNNs and Transformers, finds applications in diverse domains, including machine translation, image generation, speech synthesis, and data entity extraction.

Data Extraction 273

Data Extraction Neural Network Large Language Models NLP 273

Marktechpost

MARCH 11, 2024

Value functions, implemented with neural networks, undergo training via mean squared error regression to align with bootstrapped target values. However, upscaling value-based RL methods utilizing regression for extensive networks, like high-capacity Transformers, has posed challenges.

Neural Network 129

Neural Network Categorization Deep Learning Robotics 129

IBM Journey to AI blog

DECEMBER 20, 2023

Many retailers’ e-commerce platforms—including those of IBM, Amazon, Google, Meta and Netflix—rely on artificial neural networks (ANNs) to deliver personalized recommendations. Regression algorithms —predict output values by identifying linear relationships between real or continuous values (e.g.,

Machine Learning 230

Machine Learning Neural Network Algorithm Computer Vision 230

Unite.AI

DECEMBER 7, 2024

At its core, the Iris AI engine operates as a sophisticated neural network that continuously monitors and analyzes social signals across multiple platforms, transforming raw social data into actionable intelligence for brand protection and marketing optimization.

AI Tools 278

AI Tools Automation NLP Algorithm 278

AI Weekly

OCTOBER 17, 2024

medium.com Similarity-driven adversarial testing of neural networks As similarity is one of the key components of human cognition and categorization, the approach presents a shift towards a more human-centered security testing of deep neural networks. Explore its AI-powered versatility.

ChatGPT 207

ChatGPT Robotics Neural Network Artificial Intelligence 207

Heartbeat

JUNE 27, 2023

Photo by Resource Database on Unsplash Introduction Neural networks have been operating on graph data for over a decade now. Neural networks leverage the structure and properties of graph and work in a similar fashion. Graph Neural Networks are a class of artificial neural networks that can be represented as graphs.

Neural Network 59

Neural Network Convolutional Neural Networks Auto-classification Deep Learning 59

Pickl AI

DECEMBER 4, 2024

Summary: A perceptron is the simplest form of an artificial neural network, designed to classify input data into two categories. Developed by Frank Rosenblatt in 1957, the Perceptron is one of the earliest types of artificial neural networks and serves as a binary classifier. How Does a Perceptron Work? Colour Weight = 1.0

Neural Network 52

Neural Network Machine Learning Categorization Algorithm 52

Marktechpost

JUNE 8, 2024

Areas like CO or lattice models in physics involve discrete target distributions, which can be approximated using products of categorical distributions. Here, samples are generated by first drawing latent variables from a prior distribution, which are then processed by a neural network-based stochastic decoder.

Neural Network 128

Neural Network Categorization ML Artificial Intelligence 128

Unite.AI

MAY 3, 2024

Self-managed content refers to the use of AI and neural networks to simplify and strengthen the content creation process via smart tagging, metadata templates, and modular content. Role of AI and neural networks in self-management of digital assets Metadata is key in the success of self-managing content.

Neural Network 147

Neural Network Metadata Categorization Automation 147

Unite.AI

NOVEMBER 8, 2023

One-hot encoding is a process by which categorical variables are converted into a binary vector representation where only one bit is “hot” (set to 1) while all others are “cold” (set to 0). Functionality : Each encoder layer has self-attention mechanisms and feed-forward neural networks.

BERT 298

BERT NLP Neural Network Natural Language Processing 298

Unite.AI

MARCH 15, 2024

In recent years, groundbreaking work in AI, particularly through deep neural networks, has significantly advanced object detection. Furthermore, selected frameworks train open-vocabulary object detectors at scale, and categorize training object detectors as region-level vision-language pre-training.

Neural Network 246

Neural Network Computer Vision Categorization Algorithm 246

Marktechpost

NOVEMBER 27, 2024

Classification: Categorizing data into discrete classes (e.g., Sigmoid Kernel: Inspired by neural networks. It’s a simple yet effective algorithm, particularly well-suited for text classification problems like spam filtering, sentiment analysis, and document categorization. Document categorization.

Machine Learning 116

Machine Learning Algorithm Neural Network Convolutional Neural Networks 116

Viso.ai

JANUARY 2, 2024

In the following, we will explore Convolutional Neural Networks (CNNs), a key element in computer vision and image processing. Whether you’re a beginner or an experienced practitioner, this guide will provide insights into the mechanics of artificial neural networks and their applications. Howard et al.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Computer Vision Data Scarcity 52

Marktechpost

JANUARY 31, 2024

The inherent opacity of these models has fueled interpretability research, leveraging the unique advantages of artificial neural networks—being observable and deterministic—for empirical scrutiny. Inspired by claims suggesting universality in artificial neural networks, particularly the work by Olah et al.

Neural Network 137

Neural Network Large Language Models Categorization Automation 137

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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Convolutional Neural Networks Neural Network Natural Language Processing Deep Learning 52

ML Review

MARCH 31, 2019

We start with an image of a panda, which our neural network correctly recognizes as a “panda” with 57.7% Add a little bit of carefully constructed noise and the same neural network now thinks this is an image of a gibbon with 99.3% This is, clearly, an optical illusion — but for the neural network.

Neural Network 52

Neural Network Machine Learning Deep Learning Explainability 52

Marktechpost

JULY 21, 2023

Various activities, such as organizing large amounts into small groups and categorizing numerical quantities like numbers, are performed by our nervous system with ease but the emergence of these number sense is unknown. Analogous to the human brain’s visual cortex; V1, V2, V3, and IPS are visual processing streams in the Deep neural network.

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Convolutional Neural Networks Neural Network AI Researcher AI Research 98

Towards AI

MAY 3, 2024

After a quick search, I found an MRI dataset on Kaggle that contains brain MRI scans categorized by tumor type: three groups according to the type of tumor, and a fourth group that includes scans of healthy brains. I also found a notebook with a neural network that can categorize the images with perfect accuracy.

Neural Network 102

Neural Network Categorization Metadata AI 102

Snorkel AI

JULY 2, 2024

Extending weak supervision to non-categorical problems Our research presented in our paper “ Universalizing Weak Supervision ” aimed to extend weak supervision beyond its traditional categorical boundaries to more complex, non-categorical problems where rigid categorization isn’t practical.

Categorization 52

Categorization Neural Network Explainability Large Language Models 52

Snorkel AI

JULY 2, 2024

Extending weak supervision to non-categorical problems Our research presented in our paper “ Universalizing Weak Supervision ” aimed to extend weak supervision beyond its traditional categorical boundaries to more complex, non-categorical problems where rigid categorization isn’t practical.

Categorization 52

Categorization Neural Network Explainability Large Language Models 52

Heartbeat

MARCH 1, 2023

Tracking your image classification experiments with Comet ML Photo from nmedia on Shutterstock.com Introduction Image classification is a task that involves training a neural network to recognize and classify items in images. A dataset of labeled images is used to train the network, with each image given a particular class or label.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Auto-classification Categorization 52

Unite.AI

JULY 25, 2024

These fingerprints can then be analyzed by a neural network, unveiling previously inaccessible information about material behavior. ” This ability to recognize and categorize patterns without human intervention allows for a more comprehensive and unbiased analysis of material behavior.

Neural Network 182

Neural Network Machine Learning Artificial Intelligence Artificial Intelligence 182

Mlearning.ai

MAY 8, 2023

A comprehensive step-by-step guide with data analysis, deep learning, and regularization techniques Introduction In this article, we will use different deep-learning TensorFlow neural networks to evaluate their performances in detecting whether cell nuclei mass from breast imaging is malignant or benign. df['Unnamed: 32'].head(10)

Neural Network 52

Neural Network Deep Learning Machine Learning Categorization 52

Unite.AI

SEPTEMBER 18, 2023

Blockchain technology can be categorized primarily on the basis of the level of accessibility and control they offer, with Public, Private, and Federated being the three main types of blockchain technologies. The neural network consists of three types of layers including the hidden layer, the input payer, and the output layer.

Deep Learning 321

Deep Learning Artificial Intelligence Artificial Intelligence AI 321

Marktechpost

OCTOBER 3, 2023

This distinction is essential for a variety of uses, such as building playlists for particular objectives, concentration, or relaxation, and even as a first step in language categorization for singing, which is crucial in marketplaces with numerous languages.

Artificial Intelligence 131

Artificial Intelligence Artificial Intelligence Neural Network Categorization 131

AssemblyAI

FEBRUARY 16, 2024

Entity Detection spots and categorizes important data in your audio, like names, organizations, addresses, and more.   PII Redaction automatically finds and hides personal details like names and email addresses in transcripts to protect privacy.

Neural Network 147

Neural Network Python Categorization Generative AI 147

Marktechpost

JANUARY 14, 2024

The researchers present a categorization system that uses backbone networks to organize these methods. Most picture deblurring methods use paired images to train their neural networks. The initial step is using a neural network to estimate the blur kernel.

Deep Learning 115

Deep Learning Convolutional Neural Networks Neural Network Computer Vision 115

Unite.AI

MAY 24, 2024

Recently, Recurrent Neural Networks like methods including Mamba and RWKV have gathered significant attention owing to their promising results in large language models.

Convolutional Neural Networks 130

Convolutional Neural Networks Neural Network BERT Natural Language Processing 130

Flipboard

DECEMBER 27, 2023

Instead, programmers can train a neural network on people-like shapes until it reliably identifies human beings in subsequent video. Then they can train the neural network on more sophisticated patterns, such as people falling over, running, fighting, even arguing, or carrying a knife.

Algorithm 181

Algorithm Neural Network Software Development Categorization 181

Marktechpost

FEBRUARY 22, 2024

In computer vision, convolutional networks acquire a semantic understanding of images through extensive labeling provided by experts, such as delineating object boundaries in datasets like COCO or categorizing images in ImageNet.

Computer Vision 130

Computer Vision Natural Language Processing Neural Network Categorization 130

Mlearning.ai

FEBRUARY 28, 2023

Theoretical Explanations and Practical Examples of Correlation between Categorical and Continuous Values Without any doubt, after obtaining the dataset, giving entire data to any ML model without any data analysis methods such as missing data analysis, outlier analysis, and correlation analysis.

Categorization 52

Categorization Data Analysis Neural Network ML 52

Viso.ai

DECEMBER 19, 2023

Today, the use of convolutional neural networks (CNN) is the state-of-the-art method for image classification. Image classification is the task of categorizing and assigning labels to groups of pixels or vectors within an image dependent on particular rules. We will cover the following topics: What Is Image Classification?

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Deep Learning 98

Towards AI

JULY 9, 2024

In this sense, it is an example of artificial intelligence that is, teaching computers to see in the same way as people do, namely by identifying and categorizing objects based on semantic categories. Another method for figuring out which category a detected object belongs to is object categorization.

Convolutional Neural Networks 110

Convolutional Neural Networks ML Neural Network Computer Vision 110

Marktechpost

DECEMBER 24, 2023

These methods address the challenges of traditional approaches, offering more automated, accurate, and robust solutions for identifying and categorizing plant leaf diseases. As the demand for sustainable agriculture grows, machine learning emerges as a vital force, reshaping the future of food security and cultivation.

Machine Learning 121

Machine Learning Convolutional Neural Networks Neural Network Deep Learning 121

Unite.AI

AUGUST 28, 2023

Neural Networks & Deep Learning : Neural networks marked a turning point, mimicking human brain functions and evolving through experience. link] The process can be categorized into three agents: Execution Agent : The heart of the system, this agent leverages OpenAI’s API for task processing.

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Auto-complete ChatGPT Large Language Models Neural Network 240