KDnuggets

OCTOBER 14, 2019

A recent survey outlined the main neural architecture search methods used to automate the design of deep learning systems.

Deep Learning 174

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insideBIGDATA

NOVEMBER 30, 2023

Unfortunately, when asked to define RAG, the definitions are all over the place. In this contributed article, Magnus Revang, Chief Product Officer of Openstream.ai, points out that In the Large Language Model space, one acronym is frequently put forward as the solution to all the weaknesses. Hallucinations? Confidentiality?

Big Data 433

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IBM Journey to AI blog

MAY 10, 2024

Underpinning most artificial intelligence (AI) deep learning is a subset of machine learning that uses multi-layered neural networks to simulate the complex decision-making power of the human brain. Deep learning requires a tremendous amount of computing power.

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Towards AI

JANUARY 27, 2023

Deep Learning Explained: Perceptron The key concept behind every neural network. Source: Image by Gerd Altmann from Pixabay Nowadays, frameworks such as Keras, TensorFlow, or PyTorch provide turnkey access to most deep learning solutions without necessarily having to understand them in depth. outputs y, and weights ?

Deep Learning 96

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Analytics Vidhya

MAY 7, 2024

Either way, you will need the right resources to TRUST, LEARN and SUCCEED. If you are unable to find the right Machine Learning resource in 2024? We are here to help.

Machine Learning 328

Machine Learning Machine Learning Analytics Analytics 328

Analytics Vidhya

APRIL 15, 2024

From ChatGPT, which helps in copywriting, data analysis, and summarizing complex research papers, to Midjourney for generating high-definition images with a single prompt, and GitHub Copilot for […] The post 5 MIND-BLOWING AI Tools that Feel Illegal to Know appeared first on Analytics Vidhya.

Data Analysis 326

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Flipboard

JANUARY 22, 2023

ChatGPT is a powerful language model that uses deep learning techniques to generate human-like text. You can start right away. In case you've missed the buzz, OpenAI just publicly launched its latest language generation robot, ChatGPT. In other words, the robot is capable of answering all of your …

Deep Learning 123

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Analytics Vidhya

JANUARY 3, 2024

In this definitive guide, we will explore the various types of […] The post A Comprehensive Guide to Python Function Arguments appeared first on Analytics Vidhya. Introduction Python functions are an essential part of any programming language, allowing us to encapsulate reusable blocks of code.

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Python Analytics Analytics Deep Learning 305

Analytics Vidhya

DECEMBER 28, 2023

Further in this guide, you will explore temporal graphs in data science—definition, […] The post A Comprehensive Guide to Temporal Graphs in Data Science appeared first on Analytics Vidhya. They capture the temporal dependencies between entities and offer a robust framework for modeling and analyzing time-varying relationships.

Data Science 304

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Dataconomy

MARCH 21, 2025

Definition and significance of NLP Natural Language Processing is a subset of AI that combines computational linguistics and advanced algorithms to facilitate human-computer interaction. Approaches to NLP NLP can be broadly categorized into rule-based systems and machine learning systems.

Natural Language Processing 103

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Dataconomy

MARCH 11, 2025

Typically represented in mathematical terms, the target function establishes the foundation for how outputs are generated from inputs, effectively shaping the learning process of AI systems. Deep learning frameworks often involve more complex target functions due to their ability to process larger datasets with multiple layers of abstraction.

Machine Learning 91

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Analytics Vidhya

DECEMBER 16, 2020

Introduction We often see that when people are giving the definition of. This article was published as a part of the Data Science Blogathon. The post An Overview of Neural Approach on Pattern Recognition appeared first on Analytics Vidhya.

Data Science 271

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Data Science Dojo

SEPTEMBER 8, 2023

We’ll dive into the core concepts of AI, with a special focus on Machine Learning and Deep Learning, highlighting their essential distinctions. However, with the introduction of Deep Learning in 2018, predictive analytics in engineering underwent a transformative revolution.

Predictive Analytics 243

Predictive Analytics Analytics Analytics Deep Learning 243

Analytics Vidhya

MARCH 7, 2023

Introduction This article will provide a clear and concise definition of word meaning, highlighting its significance in language and communication. We will also discuss the various types of word meanings, such as denotative, connotative, and figurative meanings.

Analytics 250

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DrivenData Labs

MAY 12, 2025

competition, winning solutions used deep learning approaches from facial recognition tasks (particularly ArcFace and EfficientNet) to help the Bureau of Ocean and Energy Management and NOAA Fisheries monitor endangered populations of beluga whales by matching overhead photos with known individuals.

Algorithm 130

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Dataconomy

MARCH 17, 2025

PyTorch has emerged as one of the most prominent frameworks in the realm of machine learning and deep learning, captivating both researchers and developers alike. PyTorch is an open-source machine learning framework widely used for deep learning applications. What is PyTorch?

Natural Language Processing 91

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Dataconomy

MARCH 25, 2025

RMSProp is an essential optimization algorithm that has gained prominence in the fields of deep learning and machine learning. Unlike traditional methods, RMSProp adapts the learning rate of each parameter based on their historical gradients, significantly improving the training process and enhancing model performance.

Deep Learning 91

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Heartbeat

NOVEMBER 29, 2023

Two names stand out prominently in the wide realm of deep learning: TensorFlow and PyTorch. These strong frameworks have changed the field, allowing researchers and practitioners to create and deploy cutting-edge machine learning models. TensorFlow and PyTorch present distinct routes to traverse.

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Dataconomy

MARCH 27, 2025

Neural networks utilize statistical methods to learn patterns from data, while symbolic reasoning relies on explicit rules and logic to process information. Definition and purpose Neural networks are designed to mimic human brain functions using layers of interconnected nodes, processing input data through complex mathematical computations.

AI 125

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PyImageSearch

DECEMBER 23, 2024

With reaching billions, no hardware can process these operations in a definite amount of time. Do you think learning computer vision and deep learning has to be time-consuming, overwhelming, and complicated? Here youll learn how to successfully and confidently apply computer vision to your work, research, and projects.

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K-nearest Neighbors Algorithm Deep Learning Deep Learning 118

Towards AI

DECEMBER 24, 2024

While we dont think this model is AGI yet (which has wildly differing definitions in any case), we think this model is hugely significant and should be on the front page of all newspapers. It suggests that deep learning and the LLM paradigm dont have any obvious limits. Do you need to find a new career?

Deep Learning 115

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AWS Machine Learning Blog

MAY 6, 2025

Human-based model evaluation has supported custom metric definition since its launch in November 2023. At the time of writing, we dont accept custom AWS Lambda functions or endpoints for code-based custom metric evaluators.

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DagsHub

JULY 25, 2024

Source: Author Introduction Deep learning, a branch of machine learning inspired by biological neural networks, has become a key technique in artificial intelligence (AI) applications. Deep learning methods use multi-layer artificial neural networks to extract intricate patterns from large data sets.

Deep Learning 52

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Data Science Blog

FEBRUARY 23, 2023

1, Data is the new oil, but labeled data might be closer to it Even though we have been in the 3rd AI boom and machine learning is showing concrete effectiveness at a commercial level, after the first two AI booms we are facing a problem: lack of labeled data or data themselves.

Supervised Learning 264

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Towards AI

DECEMBER 24, 2024

While we dont think this model is AGI yet (which has wildly differing definitions in any case), we think this model is hugely significant and should be on the front page of all newspapers. It suggests that deep learning and the LLM paradigm dont have any obvious limits. Do you need to find a new career?

Deep Learning 104

Deep Learning Deep Learning AI AI 104

Dataconomy

APRIL 28, 2025

The Adaptive Gradient Algorithm (AdaGrad) represents a significant stride in optimization techniques, particularly in the realms of machine learning and deep learning. By dynamically adjusting the learning rates for different parameters during model training, AdaGrad helps tackle challenges of convergence and efficiency.

Algorithm 91

Algorithm Natural Language Processing Machine Learning Machine Learning 91

ML @ CMU

NOVEMBER 7, 2024

We also argue how labels should be assigned to predict the results of humanitarian demining operations, rectifying the definition of labels used in previous literature. For the Risk Modeling component, we designed a novel interpretable deep learning tabular model extending TabNet.

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Dataconomy

MARCH 6, 2025

Definition and concept of edge AI Edge AI combines advanced algorithms with localized processing capabilities, enabling devices to analyze data on-site. Innovations like federated deep learning, which allows models to learn across multiple devices while preserving privacy, promise to enhance Edge AI’s capabilities further.

AI 91

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Towards AI

JULY 20, 2023

Deep Learning for Coders: Image by Anton Maksimov juvnsky This article is an expanded guide that’s meant to help you learn what’s happening throughout the chapter. It provides definitions of terms, commands, and code that are used in the article.

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AWS Machine Learning Blog

JUNE 11, 2024

release , you can now launch Neuron DLAMIs (AWS Deep Learning AMIs) and Neuron DLCs (AWS Deep Learning Containers) with the latest released Neuron packages on the same day as the Neuron SDK release. AWS DLCs provide a set of Docker images that are pre-installed with deep learning frameworks.

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Flipboard

JUNE 20, 2023

All of the definitions were written by a human. Machine learning Machine learning is when computers use experience to improve their performance. Deep learning Deep learning is a specific type of machine learning used in the most powerful AI systems.

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AWS Machine Learning Blog

MAY 31, 2023

In late 2022, AWS announced the general availability of Amazon EC2 Trn1 instances powered by AWS Trainium accelerators, which are purpose built for high-performance deep learning training. Create a task definition to define an ML training job to be run by Amazon ECS. With containers, scaling on a cluster becomes much easier.

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Flipboard

FEBRUARY 10, 2025

For a comprehensive list of supported deep learning container images, refer to the available Amazon SageMaker Deep Learning Containers. Task definition (count_task) This is a task that we want this agent to execute. This agent is equipped with a tool called BlocksCounterTool.

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AWS Machine Learning Blog

JANUARY 27, 2025

Examples for this could include use cases like geospatial analysis, bioinformatics research, or quantum machine learning. In such cases, SageMaker allows you to extend its functionality by creating custom container images and defining custom model definitions. Write a Python model definition using the SageMaker inference.py

AWS 110

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Flipboard

MARCH 27, 2023

torch.compile torch.compile Definition Accelerating DNNs with PyTorch 2.0 In this series, you will learn about Accelerating Deep Learning Models with PyTorch 2.0. This lesson is the 1st of a 2-part series on Accelerating Deep Learning Models with PyTorch 2.0 : What’s New in PyTorch 2.0?

Deep Learning 158

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Dataconomy

MARCH 12, 2025

It provides insights into the expected performance of machine learning algorithms and sets the stage for determining the success of more advanced modeling techniques. Advanced techniques in ML Sophisticated algorithms, such as deep learning, ensemble learning, and unsupervised learning, enhance model capabilities.

Machine Learning 91

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Flipboard

NOVEMBER 27, 2023

To understand how this plays out, we will first have to look at some of the definitions introduced by Pearl. Definitions Definition 1 The probability distribution of the outcome after the intervention is given by the equation: where the distribution of the outcome is defined as the probability assigned by the model to each outcome level.

Deep Learning 91

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