Unite.AI

OCTOBER 3, 2023

This mix of affordability and efficiency not only opened up new avenues for researchers and developers but also set the stage for a new era of technological advancements in natural language processing. This mechanism is analogous to the receptive fields seen in Convolutional Neural Networks (CNNs).

Large Language Models 334

Large Language Models Convolutional Neural Networks Neural Network Natural Language Processing 334

Marktechpost

JANUARY 30, 2025

Contrastingly, agentic systems incorporate machine learning (ML) and artificial intelligence (AI) methodologies that allow them to adapt, learn from experience, and navigate uncertain environments. Natural Language Processing (NLP): Text data and voice inputs are transformed into tokens using tools like spaCy.

Robotics 116

Robotics Convolutional Neural Networks Large Language Models AI 116

Pickl AI

JANUARY 29, 2025

With the rapid advancements in Artificial Intelligence, it’s essential to gain practical experience alongside theoretical knowledge. Whether you’re interested in image recognition, natural language processing, or even creating a dating app algorithm, theres a project here for everyone.

Deep Learning 52

Deep Learning Neural Network Natural Language Processing Computer Vision 52

AssemblyAI

JANUARY 23, 2025

Modern speech recognition systems often leverage machine learning and artificial intelligence, allowing them to handle various accents, languages, and speaking styles with impressive accuracy. It works by analyzing audio signals, identifying patterns, and matching them to words and phrases using advanced algorithms.

Python 130

Python Convolutional Neural Networks Neural Network OpenAI 130

Marktechpost

APRIL 12, 2024

Deep learning architectures have revolutionized the field of artificial intelligence, offering innovative solutions for complex problems across various domains, including computer vision, natural language processing, speech recognition, and generative models.

Deep Learning 137

Deep Learning Convolutional Neural Networks Neural Network Natural Language Processing 137

Pickl AI

NOVEMBER 22, 2024

This leads to the vanishing gradient problem, making it difficult for RNNs to retain information from earlier time steps when processing long sequences. LSTMs are crucial for natural language processing tasks. Key Takeaways LSTMs address the vanishing gradient problem in RNNs. In What Applications Are LSTMS Commonly Used?

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Natural Language Processing NLP 52

Pickl AI

APRIL 6, 2025

Summary: Deep Learning vs Neural Network is a common comparison in the field of artificial intelligence, as the two terms are often used interchangeably. Introduction Deep Learning and Neural Networks are like a sports team and its star player. Is Deep Learning A Type of Neural Network?

Neural Network 52

Neural Network Deep Learning Natural Language Processing Convolutional Neural Networks 52

ODSC - Open Data Science

NOVEMBER 28, 2024

NVIDIA’s AI Tools Suite to Aid in Accelerated Humanoid Robotics Development NVIDIA’s AI tools suite may drive developers toward complex machine learning and natural language processing solutions. In all likelihood, AI technology and humanoid robotics will progress hand in hand in the coming years.

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network LLM Natural Language Processing 52

Unite.AI

AUGUST 8, 2023

In the artificial intelligence ecosystem, two models exist: discriminative and generative. A scheduler, as seen in libraries like “ diffusers “, dictates the nature of these noisy renditions based on established algorithms. Discriminative models are what most people encounter in daily life.

Generative AI 243

Generative AI ChatGPT Neural Network Convolutional Neural Networks 243

Unite.AI

NOVEMBER 6, 2023

For instance, NN used for computer vision tasks (object detection and image segmentation) are called convolutional neural networks (CNNs) , such as AlexNet , ResNet , and YOLO. Today, generative AI technology is taking neural network techniques one step further, allowing it to excel in various AI domains.

Machine Learning 204

Machine Learning Neural Network Deep Learning Convolutional Neural Networks 204

Unite.AI

AUGUST 2, 2023

Self Supervised Learning models build representations of the training data using human annotated labels, and it’s one of the major reasons behind the advancement of the NLP or Natural Language Processing , and the Computer Vision technology.

Computer Vision 246

Computer Vision Algorithm Natural Language Processing Convolutional Neural Networks 246

Marktechpost

MARCH 20, 2025

Let’s create a small dataset of abstracts from various fields: Copy Code Copied Use a different Browser abstracts = [ { "id": 1, "title": "Deep Learning for Natural Language Processing", "abstract": "This paper explores recent advances in deep learning models for natural language processing tasks.

Natural Language Processing 59

Natural Language Processing Convolutional Neural Networks Neural Network Computer Vision 59

Marktechpost

JULY 31, 2024

Learning TensorFlow enables you to create sophisticated neural networks for tasks like image recognition, natural language processing, and predictive analytics. Natural Language Processing in TensorFlow This course focuses on building natural language processing systems using TensorFlow.

Neural Network 108

Neural Network Auto-classification Natural Language Processing Deep Learning 108

Artificial Corner

JANUARY 23, 2025

Subscribe now #3 Natural Language Processing Course in Python This is a short yet useful 2-hour NLP course for anyone interested in the field of Natural Language Processing. NLP is a branch of artificial intelligence that allows machines to understand human language.

Data Science 95

Data Science Python Convolutional Neural Networks Natural Language Processing 95

Marktechpost

MAY 5, 2024

It covers topics like image processing, cluster analysis, gradient boosting, and popular libraries like scikit-learn, Spark, and Keras. and demonstrates their application in various real-world applications. The course also teaches how to implement these models using Python libraries like PyTorch.

Machine Learning 120

Machine Learning Python Neural Network Convolutional Neural Networks 120

Marktechpost

MARCH 26, 2024

The transformer architecture has improved natural language processing, with recent advancements achieved through scaling efforts from millions to billion-parameter models. Observations indicate diminishing returns with increased model depth, mirroring challenges in deep convolutional neural networks for computer vision.

Convolutional Neural Networks 131

Convolutional Neural Networks Natural Language Processing Computer Vision Neural Network 131

Pickl AI

APRIL 9, 2025

Summary: Artificial Intelligence (AI) and Deep Learning (DL) are often confused. AI vs Deep Learning is a common topic of discussion, as AI encompasses broader intelligent systems, while DL is a subset focused on neural networks. Both Drive Technological Innovation: Transform industries with intelligent systems.

Deep Learning 52

Deep Learning Artificial Intelligence Artificial Intelligence Explainability 52

Unite.AI

OCTOBER 22, 2024

Artificial Intelligence (AI) is changing our world incredibly, influencing industries like healthcare, finance, and retail. AI models like neural networks , used in applications like Natural Language Processing (NLP) and computer vision , are notorious for their high computational demands.

Neural Network 147

Neural Network Convolutional Neural Networks Deep Learning Natural Language Processing 147

Unite.AI

MAY 24, 2024

In modern machine learning and artificial intelligence frameworks, transformers are one of the most widely used components across various domains including GPT series, and BERT in Natural Language Processing, and Vision Transformers in computer vision tasks.

Convolutional Neural Networks 130

Convolutional Neural Networks Neural Network BERT Machine Learning 130

Marktechpost

MAY 24, 2024

Transformers have greatly transformed natural language processing, delivering remarkable progress across various applications. Previous studies have explored methods like backpropagation and fine-tuning to understand sparsity in convolutional neural networks.

Convolutional Neural Networks 120

Convolutional Neural Networks Neural Network Natural Language Processing Machine Learning 120

ODSC - Open Data Science

MARCH 10, 2025

Over the past decade, data science has undergone a remarkable evolution, driven by rapid advancements in machine learning, artificial intelligence, and big data technologies. By 2017, deep learning began to make waves, driven by breakthroughs in neural networks and the release of frameworks like TensorFlow.

Data Science 52

Data Science Neural Network Convolutional Neural Networks Large Language Models 52

Flipboard

MARCH 27, 2023

Project Structure Accelerating Convolutional Neural Networks Parsing Command Line Arguments and Running a Model Evaluating Convolutional Neural Networks Accelerating Vision Transformers Evaluating Vision Transformers Accelerating BERT Evaluating BERT Miscellaneous Summary Citation Information What’s New in PyTorch 2.0?

Neural Network 157

Neural Network Convolutional Neural Networks BERT Deep Learning 157

Marktechpost

DECEMBER 10, 2024

Artificial Neural Networks (ANNs) have become one of the most transformative technologies in the field of artificial intelligence (AI). 1943: McCulloch and Pitts created a mathematical model for neural networks, marking the theoretical inception of ANNs. How Do Artificial Neural Networks Work?

Neural Network 109

Neural Network Convolutional Neural Networks Natural Language Processing Algorithm 109

Unite.AI

APRIL 26, 2024

The advancements in large language models have significantly accelerated the development of natural language processing , or NLP. These extend far beyond the traditional text-based processing of LLMs to include multimodal interactions.

Large Language Models 162

Large Language Models Natural Language Processing Convolutional Neural Networks Neural Network 162

ODSC - Open Data Science

FEBRUARY 10, 2025

adults use only work when they can turn audio data into words, and then apply natural language processing (NLP) to understand it. Choose an Appropriate Algorithm As with all machine learning processes, algorithm selection is also crucial. Speech Recognition Audio analysis is central to speech and voice recognition.

Machine Learning 52

Machine Learning Convolutional Neural Networks Neural Network Natural Language Processing 52

Marktechpost

NOVEMBER 10, 2023

Traditionally, Convolutional Neural Networks (CNNs) have been the go-to models for processing image data, leveraging their ability to extract meaningful features and classify visual information.

Convolutional Neural Networks 109

Convolutional Neural Networks Computer Vision Natural Language Processing Neural Network 109

Marktechpost

JANUARY 15, 2025

These limitations are particularly significant in fields like medical imaging, autonomous driving, and natural language processing, where understanding complex patterns is essential. Recurrent Neural Networks (RNNs): Well-suited for sequential data like time series and text, RNNs retain context through loops.

Deep Learning 87

Deep Learning Neural Network Convolutional Neural Networks Natural Language Processing 87

Viso.ai

OCTOBER 9, 2024

Emotion AI, also called Affective Computing, is a rapidly growing branch of Artificial Intelligence allowing computers to analyze and understand human language nonverbal signs such as facial expressions, body language, gestures, and voice tones to assess their emotional state. What is Emotion AI?

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Emotion AI 98

Pickl AI

JULY 12, 2024

Summary: This guide explores Artificial Intelligence Using Python, from essential libraries like NumPy and Pandas to advanced techniques in machine learning and deep learning. It equips you to build and deploy intelligent systems confidently and efficiently.

Artificial Intelligence 52

Artificial Intelligence Artificial Intelligence Python Neural Network 52

Unite.AI

MARCH 26, 2024

The development of Large Language Models (LLMs) built from decoder-only transformer models has played a crucial role in transforming the Natural Language Processing (NLP) domain, as well as advancing diverse deep learning applications including reinforcement learning , time-series analysis, image processing, and much more.

Natural Language Processing 147

Natural Language Processing Neural Network Convolutional Neural Networks Large Language Models 147

IBM Journey to AI blog

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. Machine learning algorithms like Naïve Bayes and support vector machines (SVM), and deep learning models like convolutional neural networks (CNN) are frequently used for text classification.

Data Mining 170

Data Mining Convolutional Neural Networks Categorization Machine Learning 170

IBM Journey to AI blog

SEPTEMBER 24, 2024

” When Guerena’s team first started working with smartphone images, they used convolutional neural networks (CNNs). ” Guerena’s team is now working on integrating speech-to-text and natural language processing alongside computer vision in the systems they’re building.

Explainability 184

Explainability Computer Vision Convolutional Neural Networks AI 184

Marktechpost

JUNE 27, 2023

Runway Artificial intelligence (A.I.) DreamStudio DreamStudio is a computer program that uses artificial intelligence to generate pictures based on written descriptions. ChatGPT ChatGPT is a conversational user interface system powered by artificial intelligence. Descript Descript is an advanced A.I.

AI Tools 103

AI Tools Convolutional Neural Networks Artificial Intelligence Artificial Intelligence 103

Unite.AI

JULY 31, 2023

In the past decade, Artificial Intelligence (AI) and Machine Learning (ML) have seen tremendous progress. Additionally, they can generate text and speech that parallels human intelligence. Today, they are more accurate, efficient, and capable than they have ever been.

Computer Vision 246

Computer Vision Metadata Natural Language Processing ML 246

Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. Evolution of NLP Models To understand the full impact of the above evolutionary process.

NLP 98

NLP Neural Network Natural Language Processing Convolutional Neural Networks 98

Marktechpost

SEPTEMBER 17, 2024

One of the central challenges in this field is the extended time needed to train complex neural networks. In one experiment on a language task, the baseline Adam optimizer required 23,500 steps to reach the target perplexity, while NINO achieved the same performance in just 11,500 steps. reduction in training time.

Neural Network 113

Neural Network Machine Learning Convolutional Neural Networks Natural Language Processing 113

Marktechpost

JULY 16, 2023

This idea is based on “example packing,” a technique used in natural language processing to efficiently train models with inputs of varying lengths by combining several instances into a single sequence.

Convolutional Neural Networks 98

Convolutional Neural Networks Neural Network Computer Vision Natural Language Processing 98