Marktechpost

FEBRUARY 28, 2024

Parameter generation, distinct from visual generation, aims to create neural network parameters for task performance. Researchers from the National University of Singapore, University of California, Berkeley, and Meta AI Research have proposed neural network diffusion , a novel approach to parameter generation.

Neural Network 94

Neural Network Deep Learning AI Researcher AI Research 94

Marktechpost

JULY 29, 2023

Researchers at MIT has reported a method that has the potential to pave the way for machine-learning programs many times more capable than the one responsible for ChatGPT. Furthermore, their technology might consume less energy than the state-of-the-art supercomputers powering today’s machine-learning models.

Neural Network 98

Neural Network Machine Learning ChatGPT Big Data 98

Unite.AI

FEBRUARY 7, 2024

Machine learning (ML) is a powerful technology that can solve complex problems and deliver customer value. However, ML models are challenging to develop and deploy. MLOps are practices that automate and simplify ML workflows and deployments. MLOps make ML models faster, safer, and more reliable in production.

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Marktechpost

MAY 2, 2024

This study’s research area is artificial intelligence (AI) and machine learning, specifically focusing on neural networks that can understand binary code. This dataset became a substantial source of information for training machine learning models. If you like our work, you will love our newsletter.

Neural Network 102

Neural Network Machine Learning Large Language Models Automation 102

Marktechpost

MARCH 21, 2024

The fields of Machine Learning (ML) and Artificial Intelligence (AI) are significantly progressing, mainly due to the utilization of larger neural network models and the training of these models on increasingly massive datasets. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

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Machine Learning ML Neural Network Artificial Intelligence 123

Marktechpost

MAY 10, 2024

Redundant execution introduces the concept of a hybrid (convolutional) neural network designed to facilitate reliable neural network execution for safe and dependable AI. The method has scope for further extension to more complex neural network architectures and applications with additional optimization.

Convolutional Neural Networks 112

Convolutional Neural Networks Neural Network AI AI 112

Marktechpost

DECEMBER 15, 2023

Complex tasks like text or picture synthesis, segmentation, and classification are being successfully handled with the help of neural networks. However, it can take days or weeks to obtain adequate results from neural network training due to its computing demands. If you like our work, you will love our newsletter.

Neural Network 121

Neural Network Machine Learning Algorithm Deep Learning 121

Marktechpost

MAY 18, 2024

Graph Neural Networks GNNs are advanced tools for graph classification, leveraging neighborhood aggregation to update node representations iteratively. Effective graph pooling is essential for downsizing and learning representations, categorized into global and hierarchical pooling.

Neural Network 105

Neural Network Categorization Deep Learning Data Analysis 105

Mlearning.ai

FEBRUARY 22, 2023

Machine learning interview preparation: computer vision, convolutional neural network, pooling, popular convolutional neural networks Continue reading on MLearning.ai »

Convolutional Neural Networks 52

Convolutional Neural Networks Neural Network Machine Learning Computer Vision 52

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.

Machine Learning 80

Machine Learning Neural Network Natural Language Processing Python 80

Marktechpost

APRIL 26, 2024

Graphs are important in representing complex relationships in various domains like social networks, knowledge graphs, and molecular discovery. The rapid evolution and immense potential of Graph ML pose a need for conducting a comprehensive review of recent advancements in Graph ML.

Large Language Models 129

Large Language Models Machine Learning Neural Network Deep Learning 129

Marktechpost

APRIL 5, 2024

In their paper, the researchers aim to propose a theory that explains how transformers work, providing a definite perspective on the difference between traditional feedforward neural networks and transformers. Transformer architectures, exemplified by models like ChatGPT, have revolutionized natural language processing tasks.

Neural Network 125

Neural Network Natural Language Processing Categorization Explainability 125

Marktechpost

FEBRUARY 4, 2024

Meta-learning, a burgeoning field in AI research, has made significant strides in training neural networks to adapt swiftly to new tasks with minimal data. This technique centers on exposing neural networks to diverse tasks, thereby cultivating versatile representations crucial for general problem-solving.

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Neural Network Machine Learning Algorithm AI Researcher 140

Marktechpost

MAY 18, 2024

” To answer the question, they have employed Machine learning (ML)-based modeling, comparing it against traditional approaches, and Emphasized the use of measurement data for training to ensure reliable ground truth. Check out the Paper. Also, don’t forget to follow us on Twitter.

Machine Learning 79

Machine Learning Neural Network ML Artificial Intelligence 79

Marktechpost

MAY 18, 2024

Machine Learning (ML) is everywhere these days, playing a crucial role in countless fields worldwide. As ML models become more complex, it becomes more challenging to understand and interpret them. Google Researchers introduced a novel graph visualization tool tailored to the needs of ML practitioners.

Machine Learning 94

Machine Learning Neural Network ML Artificial Intelligence 94

Marktechpost

MAY 11, 2024

Graph Neural Networks (GNNs) are crucial in processing data from domains such as e-commerce and social networks because they manage complex structures. Traditionally, GNNs operate on data that fits within a system’s main memory. Check out the Paper. Join our Telegram Channel , Discord Channel , and LinkedIn Gr oup.

Neural Network 95

Neural Network ML AI AI 95

Marktechpost

JANUARY 24, 2024

However, deep neural networks are inaccurate and can produce unreliable outcomes. It is found that incorporating uncertainty quantification (UQ) into deep learning models gauges their confidence level regarding predictions. It can improve deep neural networks’ reliability in inverse imaging issues.

Neural Network 98

Neural Network Deep Learning Data Mining Natural Language Processing 98

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.

Machine Learning 84

Machine Learning ML Neural Network Algorithm 84

Flipboard

MARCH 6, 2023

With artificial intelligence and machine learning (AI/ML) processors and coprocessors roaring across the embedded edge product landscape, the quest continues for high-performance technology that can run a wide range of AI/ML models with very low power consumption. Brainchip has been marketing a …

Machine Learning 122

Machine Learning Neural Network Artificial Intelligence Artificial Intelligence 122

Marktechpost

DECEMBER 21, 2023

In machine learning, larger networks with increasing parameters are being trained. However, training such networks has become prohibitively expensive. ReLoRA accomplishes a high-rank update, delivering a performance akin to conventional neural network training. parameters. Check out the Paper and Github.

Neural Network 116

Neural Network AI AI Machine Learning 116

Marktechpost

FEBRUARY 21, 2024

Graph-based machine learning is undergoing a significant transformation, largely propelled by the introduction of Graph Neural Networks (GNNs). These networks have been pivotal in harnessing the complexity of graph-structured data, offering innovative solutions across various domains.

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Neural Network Machine Learning ML Artificial Intelligence 138

Mlearning.ai

FEBRUARY 4, 2024

This is the second part of my Neural Networks 101 series, in this blog we are going to discuss about the training of machine learning models. You can follow me on Twitter to learn more about this. Your input data travels through the neural network, layer by layer. I hope you are doing well.

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Neural Network Deep Learning Machine Learning Software Engineer 52

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.

Deep Learning 121

Deep Learning Machine Learning Python Computer Vision 121

Marktechpost

SEPTEMBER 8, 2023

Meet Equinox , a JAX library designed for numerical methods that is gaining popularity within the data science and machine learning community. It offers a versatile platform not only for neural networks but also for handling a wide range of tasks, including ODEs, SDEs, linear solves, and more.

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Neural Network Machine Learning Data Science AI Researcher 92

Marktechpost

JANUARY 13, 2024

The challenge of interpreting the workings of complex neural networks, particularly as they grow in size and sophistication, has been a persistent hurdle in artificial intelligence. The traditional methods of explaining neural networks often involve extensive human oversight, limiting scalability.

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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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Neural Network Natural Language Processing AI AI 107

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.

Machine Learning 95

Machine Learning ML Neural Network Natural Language Processing 95

Marktechpost

DECEMBER 27, 2023

A challenge AI engineers face in machine learning is the need for a complex infrastructure to manage models. This problem can be time-consuming and resource-intensive, making it a hurdle for efficient machine-learning operations. PostgresML has several noteworthy features that make it stand out in machine learning.

Machine Learning 124

Machine Learning ML Python Neural Network 124

Marktechpost

DECEMBER 30, 2023

The remarkable potentials of Artificial Intelligence (AI) and Deep Learning have paved the way for a variety of fields ranging from computer vision and language modeling to healthcare, biology, and whatnot. SciML consists of three primary subfields, which include PDE solvers, PDE discovery, and operator learning.

Neural Network 121

Neural Network Deep Learning Computer Vision Machine Learning 121

Marktechpost

APRIL 11, 2024

MIT researchers have proposed a method that combines first-principles calculations and machine learning to address the challenge of computationally expensive and intractable calculations required to understand the thermal conductivity of semiconductors, specifically focusing on diamonds.

Machine Learning 96

Machine Learning Convolutional Neural Networks Neural Network AI 96

Marktechpost

OCTOBER 28, 2023

In the world of biological research, machine-learning models are making significant strides in advancing our understanding of complex processes, with a particular focus on RNA splicing. Machine learning models like neural networks have been instrumental in advancing scientific discovery and experimental design in biological sciences.

Neural Network 114

Neural Network Explainability Machine Learning Python 114

Marktechpost

FEBRUARY 8, 2024

With the world of computational science continually evolving, physics-informed neural networks (PINNs) stand out as a groundbreaking approach for tackling forward and inverse problems governed by partial differential equations (PDEs). Join our 36k+ ML SubReddit , 41k+ Facebook Community, Discord Channel , and LinkedIn Gr oup.

Neural Network 128

Neural Network Deep Learning AI AI 128

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.

Machine Learning 129

Machine Learning ML Algorithm Chatbots 129

Towards AI

APRIL 8, 2024

Interconnected graphical data is all around us, ranging from molecular structures to social networks and design structures of cities. Graph Neural Networks (GNNs) are emerging as a powerful method of modeling and learning the spatial and graphical structure of such data. An illustration of GNN: Figure 1.

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Neural Network Explainability ML AI 84

Marktechpost

MARCH 9, 2024

The evolution of artificial intelligence, particularly in the realm of neural networks, has significantly advanced our data processing and analysis capabilities. Among these advancements, the efficiency of training and deploying deep neural networks has become a paramount focus.

Neural Network 129

Neural Network Python Deep Learning Artificial Intelligence 129

Analytics Vidhya

APRIL 24, 2023

Introduction We live in a world where social media platforms shape our interests, tailor our news feeds, and provide customized content, all thanks to machine learning! With machine learning (ML), a branch of artificial intelligence (AI), software programs can predict outcomes more accurately without being explicitly instructed.

Machine Learning 253

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Towards AI

APRIL 7, 2024

With the emergence of ARCGISpro which will replace ArcMap by 2026 mainly focusing on data science and machine learning, all the signs that machine learning is the future of GIS and you might have to learn some principles of data science, but where do you start, let us have a look.

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