Dataconomy

MARCH 19, 2025

Tensor Processing Units (TPUs) represent a significant leap in hardware specifically designed for machine learning tasks. They are essential for processing large amounts of data efficiently, particularly in deep learning applications. TPUs are specialized hardware designed to accelerate and optimize machine learning workloads.

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ML @ CMU

JANUARY 2, 2025

We hypothesize that this architecture enables higher efficiency in learning the structure of natural tasks and better generalization in tasks with a similar structure than those with less specialized modules. What are the brain’s useful inductive biases? 2018 ) to enhance training (see Materials and Methods in Zhang et al.,

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Dataconomy

APRIL 3, 2025

In his thesis, A Context-Based Cross-Domain Collaborative Filtering Approach in Folksonomies , Harshit explored the intricacies of machine learning and recommendation systems, laying a solid foundation for his contributions to scalable systems and marketing technology.

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Dataconomy

MARCH 20, 2025

TensorFlow has revolutionized the field of machine learning and deep learning since its inception. TensorFlow is an open-source framework designed for machine learning and deep learning applications. Released as open-source in 2015 under the Apache 2.0 in early 2017.

Machine Learning 91

Machine Learning Machine Learning Deep Learning Deep Learning 91

Towards AI

OCTOBER 10, 2024

The evolution of Large Language Models (LLMs) allowed for the next level of understanding and information extraction that classical NLP algorithms struggle with. Advances in Neural Information Processing Systems 28 (NIPS 2015). But often, these methods fail on more complex tasks.

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Dataconomy

OCTOBER 2, 2024

Kingma, is a prominent figure in the field of artificial intelligence and machine learning. cum laude in machine learning from the University of Amsterdam in 2017. His academic work, particularly in deep learning and generative models, has had a profound impact on the AI community. ” Who is Durk Kingma?

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Data Science Dojo

DECEMBER 8, 2023

Counting Shots, Making Strides: Zero, One and Few-Shot Learning Unleashed In the dynamic field of artificial intelligence, traditional machine learning, reliant on extensive labeled datasets, has given way to transformative learning paradigms. Welcome to the frontier of machine learning innovation!

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AWS Machine Learning Blog

APRIL 7, 2025

This approach allows for greater flexibility and integration with existing AI and machine learning (AI/ML) workflows and pipelines. Chakravarthy Nagarajan is a Principal Solutions Architect specializing in machine learning, big data, and high performance computing. billion to a projected $574.78

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AWS Machine Learning Blog

DECEMBER 7, 2023

Getir was founded in 2015 and operates in Turkey, the UK, the Netherlands, Germany, and the United States. Amazon Forecast is a fully managed service that uses machine learning (ML) algorithms to deliver highly accurate time series forecasts. Getir is the pioneer of ultrafast grocery delivery.

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AWS Machine Learning Blog

JUNE 3, 2025

For over a decade in the world of technology, Taras has led everything from tight-knit agile teams of 5 or more to a company of 90 people that became the best small IT company in Ukraine under 100 people in 2015. Taras is an AWS Certified ML Engineer Associate. Anton Garvanko is a Senior Analytics Sales Specialist for Europe North at AWS.

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AWS Machine Learning Blog

OCTOBER 5, 2023

Before that, he worked on developing machine learning methods for fraud detection for Amazon Fraud Detector. He is passionate about applying machine learning, optimization, and generative AI techniques to various real-world problems. He focuses on developing scalable machine learning algorithms.

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Pickl AI

JANUARY 23, 2023

Introduction to Machine Learning Frameworks In the present world, almost every organization is making use of machine learning and artificial intelligence in order to stay ahead of the competition. So, let us see the most popular and best machine learning frameworks and their uses.

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AWS Machine Learning Blog

OCTOBER 23, 2024

At its core, Amazon Bedrock provides the foundational infrastructure for robust performance, security, and scalability for deploying machine learning (ML) models. Dhawal Patel is a Principal Machine Learning Architect at AWS. He currently is working on Generative AI for data integration.

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Flipboard

JUNE 20, 2023

Machine learning Machine learning is when computers use experience to improve their performance. Rather than humans programming computers with specific step-by-step instructions on how to complete a task, in machine learning a human provides the AI with data and asks it to achieve a certain outcome via an algorithm.

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Towards AI

FEBRUARY 14, 2023

It involves using machine learning algorithms to generate new data based on existing data. Generative AI is a subset of artificial intelligence (AI) that involves using algorithms to create new data. Generative AI works by training algorithms on large datasets, which the algorithm can then use to generate new data.

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AWS Machine Learning Blog

MAY 15, 2023

Getir was founded in 2015 and operates in Turkey, the UK, the Netherlands, Germany, France, Spain, Italy, Portugal, and the United States. Algorithm Selection Amazon Forecast has six built-in algorithms ( ARIMA , ETS , NPTS , Prophet , DeepAR+ , CNN-QR ), which are clustered into two groups: statististical and deep/neural network.

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Algorithm Data Scientist Machine Learning Machine Learning 100

AWS Machine Learning Blog

DECEMBER 4, 2023

Established in 2015, Getir has positioned itself as the trailblazer in the sphere of ultrafast grocery delivery. We capitalized on the powerful tools provided by AWS to tackle this challenge and effectively navigate the complex field of machine learning (ML) and predictive analytics.

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AWS Machine Learning Blog

NOVEMBER 26, 2024

He is passionate about generative AI and is helping customers unlock business potential and drive actionable outcomes with machine learning at scale. You can also ask the model to combine its knowledge with the knowledge from the graph. Santosh Kulkarni is an Senior Solutions Architect at Amazon Web Services specializing in AI/ML.

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Smart Data Collective

JUNE 26, 2019

Get Rid of Blind Spots in Statistical Models With Machine Learning. RiskSpan is a company that built a machine learning algorithm that can flag error-prone parts of a statistical model and indicate which associated outputs may be unreliable. This way of using machine learning is still in its early stages.

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AWS Machine Learning Blog

NOVEMBER 19, 2024

This year, generative AI and machine learning (ML) will again be in focus, with exciting keynote announcements and a variety of sessions showcasing insights from AWS experts, customer stories, and hands-on experiences with AWS services.

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Towards AI

JANUARY 10, 2024

From 2005 to 2015, I taught data science classes to groups within corporations. All were curious, with a keen desire to learn new techniques to better do their jobs. But the task of teaching data, syntax, algorithms, and applications within 1–3 days was daunting. I was lucky that my participants were bright and motivated.

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Towards AI

APRIL 23, 2024

Neural Style Transfer (NST) was born in 2015 [2], slightly later than GAN. It is one of the first algorithms to combine images based on deep learning. However, generative models is not a new term and it has come a long way since Generative Adversarial Network (GAN) was published in 2014 [1].

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PyImageSearch

NOVEMBER 13, 2023

For example, image classification, image search engines (also known as content-based image retrieval, or CBIR), simultaneous localization and mapping (SLAM), and image segmentation, to name a few, have all been changed since the latest resurgence in neural networks and deep learning. 2015 ), SSD ( Fei-Fei et al., probability).

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Towards AI

FEBRUARY 3, 2024

(Left) Photo by Pawel Czerwinski on Unsplash U+007C (Right) Unsplash Image adjusted by the showcased algorithm Introduction It’s been a while since I created this package ‘easy-explain’ and published on Pypi. A few weeks ago, I needed an explainability algorithm for a YoloV8 model. PLoS ONE 10(7), e0130140 (2015) [2] Montavon, G.,

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Flipboard

MAY 30, 2025

Throughout her career, she has shared her expertise at numerous conferences and has authored several blogs in the Machine Learning and Generative AI domains. She works on developing solutions for Responsible AI, focusing on algorithmic fairness, veracity of large language models, and explainability.

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Smart Data Collective

JUNE 14, 2019

A number of new data algorithms are being used to make digital calendars more effective. Machine learning algorithms make it easier to plan your schedule, because they can help optimize your schedule. In 2015, Gartner wrote a great piece on the proliferation of big data and its role in facilitating organization.

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AWS Machine Learning Blog

APRIL 25, 2024

The most common techniques used for extractive summarization are term frequency-inverse document frequency (TF-IDF), sentence scoring, text rank algorithm, and supervised machine learning (ML). Use the evaluation algorithm with either built-in or custom datasets to evaluate your LLM model.

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AWS Machine Learning Blog

FEBRUARY 28, 2023

In today’s highly competitive market, performing data analytics using machine learning (ML) models has become a necessity for organizations. One of the challenges of working with categorical data is that it is not as amenable to being used in many machine learning algorithms.

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AWS Machine Learning Blog

OCTOBER 9, 2023

Users Amazon Personalize need to upload data containing their own customer’s interactions in order for the model to be able to learn these behavioral trends. A data flow defines a series of transformations and analyses on data to prepare it to create a machine learning model. References [1] Maxwell Harper and Joseph A.

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AWS Machine Learning Blog

JANUARY 13, 2023

To mitigate these challenges, we propose a federated learning (FL) framework, based on open-source FedML on AWS, which enables analyzing sensitive HCLS data. It involves training a global machine learning (ML) model from distributed health data held locally at different sites. Define the model. Plos one 15.7 2020): e0235424.

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Dataconomy

MAY 8, 2023

AI drawing generators use machine learning algorithms to produce artwork What is AI drawing? You might think of AI drawing as a generative art where the artist combines data and algorithms to create something completely new. But first, let’s take a closer look at what it is. Do not get into a tizzle!

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Mlearning.ai

MARCH 9, 2023

Automated algorithms for image segmentation have been developed based on various techniques, including clustering, thresholding, and machine learning (Arbeláez et al., The MBD algorithm then searches for a subset of nodes (i.e., 2015; Huang et al., 2012; Otsu, 1979; Long et al., 2018; Sitawarin et al.,

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Dataconomy

MAY 10, 2023

Predictive analytics: Open source BI software can use algorithms and machine learning to analyze historical data and identify patterns that can be used to predict future trends and outcomes. This allows users to create and share insights with the entire team, promoting collaboration and informed decision-making.

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AWS Machine Learning Blog

AUGUST 11, 2023

Natural language processing (NLP) is the field in machine learning (ML) concerned with giving computers the ability to understand text and spoken words in the same way as human beings can. For this solution, we use the 2015 New Year’s Resolutions dataset to classify resolutions.

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IBM Journey to AI blog

AUGUST 11, 2023

Machine learning (ML), a subset of artificial intelligence (AI), is an important piece of data-driven innovation. Machine learning engineers take massive datasets and use statistical methods to create algorithms that are trained to find patterns and uncover key insights in data mining projects. What is MLOps?

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Smart Data Collective

FEBRUARY 18, 2020

These companies use the widest array of big data and machine learning algorithms to deliver value to their user base. Back in 2015 for example, consumers rated live chat the highest compared to any other customer service touchpoint according to the latest Customer Service Benchmark results from Maru/Matchbox.

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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.

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