ODSC - Open Data Science

APRIL 28, 2023

Be sure to check out her talk, “ Power trusted AI/ML Outcomes with Data Integrity ,” there! Due to the tsunami of data available to organizations today, artificial intelligence (AI) and machine learning (ML) are increasingly important to businesses seeking competitive advantage through digital transformation.

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ODSC - Open Data Science

MARCH 12, 2025

By analyzing conference session titles and abstracts from 2018 to 2024, we can trace the rise and fall of key trends that shaped the industry. 20212024: Interest declined as deep learning and pre-trained models took over, automating many tasks previously handled by classical ML techniques.

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ODSC - Open Data Science

MARCH 22, 2023

Be sure to check out his session, “ Improving ML Datasets with Cleanlab, a Standard Framework for Data-Centric AI ,” there! Anybody who has worked on a real-world ML project knows how messy data can be. Everybody knows you need to clean your data to get good ML performance. A common gripe I hear is: “Garbage in, garbage out.

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Hacker News

JANUARY 26, 2024

As the number of accepted papers at AI and ML conferences reaches into the thousands, it has become unclear how researchers access and read research publications. In this paper, we investigate the role of social media influencers in enhancing the visibility of machine learning research, particularly the citation counts of papers they share.

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Machine Learning Machine Learning ML ML 138

Data Science Dojo

SEPTEMBER 8, 2023

However, with the introduction of Deep Learning in 2018, predictive analytics in engineering underwent a transformative revolution. Machine Learning and Deep Learning: The Power Duo Machine Learning (ML) and Deep Learning (DL) are two critical branches of AI that bring exceptional capabilities to predictive analytics.

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Google Research AI blog

MAY 15, 2023

This became apparent in 2018, when the Gender Shades study highlighted that computer vision systems struggled to detect people with darker skin tones, and performed particularly poorly for women with darker skin tones. How do we effectively annotate skin tone for use in inclusive machine learning (ML)?

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Flipboard

JANUARY 14, 2025

His work on the attention mechanism and latent variable models received an Outstanding Paper Award at ACL 2017 and the Best Paper Award for JNLP in 2018 and 2019. She has industry experience, multiple first-author publications in top ML/NLP conferences, and strong foundation in mathematics and algorithms. She obtained her Ph.D.

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Dataconomy

MARCH 19, 2025

By 2018, these powerful tools were made available for third-party use, marking a significant milestone in the accessibility of high-performance computing resources. Their architecture is less suited to the large-scale matrix operations that are typical in modern ML applications.

Machine Learning 91

Machine Learning Machine Learning Natural Language Processing Deep Learning 91

Flipboard

MAY 29, 2025

Custom geospatial machine learning : Fine-tune a specialized regression, classification, or segmentation model for geospatial machine learning (ML) tasks. Our solution implements a timeline view of Sentinel-2 satellite observations from 2018 to present. Karsten holds a PhD in applied ML.

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Dataconomy

MARCH 19, 2025

Formerly known as Google Research, it was rebranded during the 2018 Google I/O conference. Data science services Through Google Cloud, users can access ML infrastructure and data science capabilities, empowering organizations to leverage AI for their specific needs.

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AWS Machine Learning Blog

AUGUST 29, 2024

The AWS DeepRacer League is the world’s first autonomous racing league, open to everyone and powered by machine learning (ML). AWS DeepRacer brings builders together from around the world, creating a community where you learn ML hands-on through friendly autonomous racing competitions.

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Towards AI

NOVEMBER 16, 2024

Ba, “On solving minimax optimization locally: A follow-the-ridge approach,” arXiv preprint arXiv:1910.07512,2019.[10] Daskalakis and I. Panageas, “The limit points of (optimistic) gradient descent in min-max optimization,” Advances in neural informationprocessing systems, vol. Mescheder, S. Nowozin, and A. Balduzzi, S. Racaniere, J. Martens, J.

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Dataconomy

MARCH 12, 2025

Background and context of model cards The concept of model cards was introduced by Google in 2018, reflecting the growing need for responsible AI practices as machine learning technologies gained momentum, particularly with large language models (LLMs). This detailed documentation is invaluable for developers, users, and regulators alike.

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Machine Learning Machine Learning AI AI 91

Flipboard

APRIL 13, 2023

The seeds of a machine learning (ML) paradigm shift have existed for decades, but with the ready availability of scalable compute capacity, a massive proliferation of data, and the rapid advancement of ML technologies, customers across industries are transforming their businesses.

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Smart Data Collective

OCTOBER 8, 2021

This article looks at how genetic algorithms (GA) and machine learning (ML) can help hedge fund organizations. As such, over 56% of hedge fund managers use AI and ML when making investment decisions. This is according to Barclay Hedge founder and President Sol Waksman in his July 2018 statement. Let me walk you through these.

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AWS Machine Learning Blog

APRIL 19, 2023

Since 2018, our team has been developing a variety of ML models to enable betting products for NFL and NCAA football. These models are then pushed to an Amazon Simple Storage Service (Amazon S3) bucket using DVC, a version control tool for ML models. Business requirements We are the US squad of the Sportradar AI department.

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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. By providing multiple access points, SageMaker JumpStart helps you seamlessly incorporate pre-trained models into your AI/ML development efforts, regardless of your preferred interface or workflow.

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AWS Machine Learning Blog

SEPTEMBER 19, 2023

Quantitative modeling and forecasting – Generative models can synthesize large volumes of financial data to train machine learning (ML) models for applications like stock price forecasting, portfolio optimization, risk modeling, and more. Multi-modal models that understand diverse data sources can provide more robust forecasts. WWW: $85.91

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AWS Machine Learning Blog

NOVEMBER 26, 2024

By harnessing the power of threat intelligence, machine learning (ML), and artificial intelligence (AI), Sophos delivers a comprehensive range of advanced products and services. The Sophos Artificial Intelligence (AI) group (SophosAI) oversees the development and maintenance of Sophos’s major ML security technology.

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Machine Learning Machine Learning SQL ML 103

Flipboard

FEBRUARY 2, 2023

With advanced analytics derived from machine learning (ML), the NFL is creating new ways to quantify football, and to provide fans with the tools needed to increase their knowledge of the games within the game of football. We then explain the details of the ML methodology and model training procedures.

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Cross Validation ML ML Machine Learning 122

AWS Machine Learning Blog

FEBRUARY 6, 2024

To support overarching pharmacovigilance activities, our pharmaceutical customers want to use the power of machine learning (ML) to automate the adverse event detection from various data sources, such as social media feeds, phone calls, emails, and handwritten notes, and trigger appropriate actions.

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Flipboard

MAY 31, 2025

This new equation demonstrated superior performance compared with the direct strength method (DSM) equations specified in the American (AISI S100-16) and Australian/New Zealand (AS/NZS 4600:2018) standazrds. In addition, machine learning (ML) techniques were employed to forecast the load-bearing capacity of cold-formed sections.

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Machine Learning Machine Learning ML ML 65

AWS Machine Learning Blog

APRIL 11, 2025

Announced at re:Invent 2018, it puts machine learning in the hands of every developer through the fun and excitement of developing and racing self-driving remote control cars. Idries is the Product Marketing Manager for AWS AI/ML Gamified Learning Programs.

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ODSC - Open Data Science

SEPTEMBER 21, 2023

Secondly, to be a successful ML engineer in the real world, you cannot just understand the technology; you must understand the business. Some typical examples are given in the following table, along with some discussion as to whether or not ML would be an appropriate tool for solving the problem: Figure 1.1:

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Machine Learning Machine Learning ML ML 98

Tableau

DECEMBER 1, 2021

April 2018), which focused on users who do understand joins and curating federated data sources. Jan 2018), which supercharged Tableau extracts with an in-memory data engine technology, designed for fast data ingest and analytical query processing on large or complex data sets. Visual encoding is key to explaining ML models to humans.

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IBM Journey to AI blog

MARCH 21, 2024

5G, or fifth-generation mobile technology , is a new specification for wireless networks developed in 2018 by the 3rd Generation Partnership Project (3DPP) to guide the development of devices, including smartphones, PCs, tablets and more, that are designed to run on 5G networks. What is 5G?

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ODSC - Open Data Science

APRIL 17, 2023

Source Purpose of Using DevSecOps in Traditional and ML Applications The DevSecOps practices are different in traditional and ML applications as each comes with different challenges. The characteristics which we saw for DevSecOps for traditional applications also apply to ML-based applications.

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ML @ CMU

OCTOBER 7, 2024

CVPR 2018 ] uses a pre-trained image encoder to embed and compare image features, with higher similarity indicating the images look alike. As text-to-visual models advance, evaluating them has become a challenging task. OpenAI 2021 ]. Esser et al., Scaling Rectified Flow Transformers for High-Resolution Image Synthesis. Stability AI 2024.

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AWS Machine Learning Blog

JUNE 26, 2024

This blog is part of the series, Generative AI and AI/ML in Capital Markets and Financial Services. Prompt the agent to build an optimal portfolio using the collected data What are the closing prices of stocks AAAA, WWW, DDD in year 2018? Sovik has published articles and holds a patent in ML model monitoring.

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DataRobot Blog

APRIL 1, 2018

Today’s data management and analytics products have infused artificial intelligence (AI) and machine learning (ML) algorithms into their core capabilities. 2] Gartner, Five Reasons to Begin Converging Application and Data Integration , Published: 12 March 2015 Refreshed: 05 February 2018, Analyst(s): Eric Thoo | Keith Guttridge. [3]

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Towards AI

JULY 20, 2023

It’s also an area that stands to benefit most from automated or semi-automated machine learning (ML) and natural language processing (NLP) techniques. Over the past several years, researchers have increasingly attempted to improve the data extraction process through various ML techniques. This study by Bui et al.

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SAS Software

FEBRUARY 13, 2023

GARP and SAS partnered for a survey in 2018 to understand the use of AI & ML models in risk management. Since then, we've seen an increasing demand in the market to credit risk transformation projects (CRTs). Because of that, the survey was expanded in 2022 and has been extended to [.]

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AWS Machine Learning Blog

APRIL 6, 2023

& AWS Machine Learning Solutions Lab (MLSL) Machine learning (ML) is being used across a wide range of industries to extract actionable insights from data to streamline processes and improve revenue generation. We trained three models using data from 2011–2018 and predicted the sales values until 2021.

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Machine Learning Machine Learning ML ML 113

Data Science 101

APRIL 26, 2019

Go Machine Learning Projects (2018) – this book uses gonum and gorgonia in the examples Machine Learning with Go (2017). Golang Data Science Books. There have even been a couple books written about the topic. Thoughts from the Community. Reasons Not to use Golang for Data Science.

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AWS Machine Learning Blog

MARCH 8, 2023

MPII is using a machine learning (ML) bid optimization engine to inform upstream decision-making processes in power asset management and trading. MPII’s bid optimization engine solution uses ML models to generate optimal bids for participation in different markets. Data comes from disparate sources in a number of formats.

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AWS Machine Learning Machine Learning Analytics 101

AWS Machine Learning Blog

FEBRUARY 10, 2023

Through a collaboration between the Next Gen Stats team and the Amazon ML Solutions Lab , we have developed the machine learning (ML)-powered stat of coverage classification that accurately identifies the defense coverage scheme based on the player tracking data. In this post, we deep dive into the technical details of this ML model.

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ML @ CMU

DECEMBER 29, 2023

Traditional distributed ML assumes each worker/client has a random (identically distributed) sample of the training data. 2018) ) We report the error rate of each HP tuning method (y-axis) at a given budget of rounds (x-axis). Heterogeneity. Source: Hyperband (Li et al.

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