Marktechpost

SEPTEMBER 26, 2023

Many graphical models are designed to work exclusively with continuous or categorical variables, limiting their applicability to data that spans different types. Moreover, specific restrictions, such as continuous variables not being allowed as parents of categorical variables in directed acyclic graphs (DAGs), can hinder their flexibility.

Neural Network 136

Neural Network Categorization Data Scientist Data Analysis 136

Marktechpost

NOVEMBER 26, 2023

Neural network architectures, particularly created and trained for few-shot knowledge the ability to learn a desired behavior from a small number of examples, were the first to exhibit this capability. Due to these convincing discoveries, emergent capabilities in massive neural networks have been the subject of study.

Neural Network 133

Neural Network Categorization AI Research AI Researcher 133

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

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.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Natural Language Processing Deep Learning 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

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

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 287

Neural Network Categorization Deep Learning NLP 287

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

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

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 127

Neural Network Categorization Deep Learning Robotics 127

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 202

ChatGPT Robotics Neural Network Artificial Intelligence 202

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

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

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

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 243

Machine Learning Neural Network Algorithm Computer Vision 243

Viso.ai

OCTOBER 10, 2024

The identification of regularities in data can then be used to make predictions, categorize information, and improve decision-making processes. While explorative pattern recognition aims to identify data patterns in general, descriptive pattern recognition starts by categorizing the detected patterns.

Neural Network 98

Neural Network Computer Vision Deep Learning Machine Learning 98

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.

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Data Extraction Neural Network Large Language Models NLP 273

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.

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network AI Research AI Researcher 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 75

Neural Network Categorization Metadata AI 75

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

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.

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Convolutional Neural Networks Neural Network BERT Natural Language Processing 130

Marktechpost

NOVEMBER 11, 2024

Seaborn simplifies the process of creating complex visualizations like: Heatmaps Scatter plots Time series plots Distribution plots Categorical plots 5. TensorFlow offers a flexible and scalable platform for building and training complex neural networks.

Data Analysis 88

Data Analysis Python Natural Language Processing Computer Vision 88

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 133

Neural Network Large Language Models Categorization Automation 133

NYU Center for Data Science

FEBRUARY 14, 2024

Davidson’s upcoming paper, “Spatial Relation Categorization in Infants and Deep Neural Networks,” co-authored with CDS Assistant Professor of Psychology and Data Science Brenden Lake and former CDS Research Scientist Emin Orhan , is set for publication in Cognition in early 2024.

Categorization 73

Categorization Neural Network Computer Vision Big Data 73

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 85

Convolutional Neural Networks ML Neural Network Computer Vision 85

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

Pickl AI

AUGUST 28, 2024

Unlike regression, which deals with continuous output variables, classification involves predicting categorical output variables. Examples include Logistic Regression, Support Vector Machines (SVM), Decision Trees, and Artificial Neural Networks. They are easy to interpret and can handle both categorical and numerical data.

Machine Learning 52

Machine Learning Algorithm Categorization Neural Network 52

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

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

Unite.AI

JANUARY 19, 2024

Traditionally, models for single-view object reconstruction built on convolutional neural networks have shown remarkable performance in reconstruction tasks. Moreover, the performance of modern convolutional neural networks in single-view 3D object reconstruction can be surpassed without explicitly inferring the 3D object structure.

Convolutional Neural Networks 130

Convolutional Neural Networks Neural Network Explainability Categorization 130

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

Pickl AI

NOVEMBER 20, 2024

Example In Deep Learning, neural networks use matrices to represent weights between layers. The forward pass through the network involves matrix multiplication to compute outputs from inputs. Neural Networks Neural networks utilize Linear Algebra extensively through layers represented as matrices.

Machine Learning 52

Machine Learning Neural Network Natural Language Processing Convolutional Neural Networks 52

PyImageSearch

NOVEMBER 18, 2024

An effective IDS could have detected the unusual network behavior associated with the ransomware’s propagation, allowing organizations to isolate affected systems and prevent further spread. Autoencoders ( Figure 3 ) are a type of neural network used for unsupervised learning, particularly well-suited for anomaly detection.

Computer Vision 83

Computer Vision Neural Network Categorization Deep Learning 83

Marktechpost

JULY 19, 2024

Traditional text-to-SQL systems using deep neural networks and human engineering have succeeded. Using long short-term memory (LSTM) and transformer deep neural networks, among others, enhanced the ability to generate SQL queries from plain English.

LLM 105

LLM Neural Network Large Language Models Natural Language Processing 105

Marktechpost

OCTOBER 14, 2024

raising widespread concerns about privacy threats of Deep Neural Networks (DNNs). Although to defend against MI attacks, most existing methods can be categorized into two types: model output processing and robust model training.

Categorization 97

Categorization Neural Network Inference Engine AI 97

Marktechpost

OCTOBER 15, 2024

XAI, or Explainable AI, brings about a paradigm shift in neural networks that emphasizes the need to explain the decision-making processes of neural networks, which are well-known black boxes. Additionally, a metric can be categorized into three types: ground_truth, downstream_evaluation, or heuristic.

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Explainable AI Explainability Python Neural Network 59