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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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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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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Dataconomy

JUNE 30, 2021

Big data is one of the most rapidly growing industries in the world and was valued at $169 billion in 2018, with expectations to approach the $300 billion mark by the end of next year. Even with such monetary influence in the world already, the industry is still figuring itself.

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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 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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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

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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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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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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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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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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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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DagsHub

JUNE 3, 2024

In 2018, there were extensive news reports that an Uber self-driving car made an accident with a pedestrian in Tempe, Arizona. The pedestrian died, and investigators found that there was an issue with the machine learning (ML) model in the car, so it failed to identify the pedestrian beforehand. Read more about benchmarking ML models.

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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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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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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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Mlearning.ai

MAY 15, 2023

describe() count 9994 mean 2017-04-30 05:17:08.056834048 min 2015-01-03 00:00:00 25% 2016-05-23 00:00:00 50% 2017-06-26 00:00:00 75% 2018-05-14 00:00:00 max 2018-12-30 00:00:00 Name: Order Date, dtype: object Average sales per year df['year'] = df['Order Date'].apply(lambda Yearly average sales. Convert it into a graph.

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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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Dataconomy

FEBRUARY 14, 2024

In the wake of the Mozilla layoffs, the company behind the famous browser has showed revisions to its product strategy ( Image credit ) Additionally, Mozilla has decided to discontinue Hubs, its 3D virtual environment introduced in 2018, and reduce its commitment to the mozilla.social Mastodon instance.

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AWS Machine Learning Blog

FEBRUARY 5, 2024

SageMaker geospatial capabilities make it easy for data scientists and machine learning (ML) engineers to build, train, and deploy models using geospatial data. Incorporating ML with geospatial data enhances the capability to detect anomalies and unusual patterns systematically, which is essential for early warning systems.

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How to Learn Machine Learning

OCTOBER 10, 2024

The quality of your training data in Machine Learning (ML) can make or break your entire project. Real-Life Examples of Poor Training Data in Machine Learning Amazon’s Hiring Algorithm Disaster In 2018, Amazon made headlines for developing an AI-powered hiring tool to screen job applicants. Let’s explore some real-world failures.

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Mlearning.ai

MARCH 15, 2023

Emergence Google coined the term federated learning (FL) during the Cambridge Analytical scandal of 2018. The ML model is then used by the user through an API by sending a request to access a specific feature. The aggregated updates are used to create an improved central ML model.

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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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IBM Journey to AI blog

MARCH 8, 2024

Currently, other transformational technologies like artificial intelligence (AI), the Internet of Things (IoT ) and machine learning (ML) require much faster speeds to function than 3G and 4G networks offer. As mobile technology has expanded over the years, the amount of data users generate every day has increased exponentially.

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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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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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AWS Machine Learning Blog

SEPTEMBER 11, 2024

These activities cover disparate fields such as basic data processing, analytics, and machine learning (ML). ML is often associated with PBAs, so we start this post with an illustrative figure. The ML paradigm is learning followed by inference. The union of advances in hardware and ML has led us to the current day.

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Towards AI

JULY 4, 2024

If you are good with Python, AI, ML, APIs, py-cord, or setting up a machine/server, connect with him in the Discord thread! Introduced in 2018, BERT has been a topic of interest for many, with many articles and YouTube videos attempting to break it down. Keep an eye on this section, too — we share cool opportunities every week!

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Heartbeat

MARCH 22, 2023

ML models use loss functions to help choose the model that is creating the best model fit for a given set of data (actual values are the most like the estimated values). A loss function (sometimes called an error function), it is a measure of the difference between the actual values and the estimated values in your model.

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AWS Machine Learning Blog

MAY 14, 2024

RLHF is a technique that combines rewards and comparisons, with human feedback to pre-train or fine-tune a machine learning (ML) model. Response before RLHF : SageMaker stores code in ML storage volumes Response after RLHF : SageMaker stores code in ML storage volumes, secured by security groups and optionally encrypted at rest.

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AWS Machine Learning Blog

APRIL 3, 2023

Causal inference Causality is all about understanding change, but how to formalize this in statistics and machine learning (ML) is not a trivial exercise. Note that this solution is currently available in the US West (Oregon) Region only. In this crop yield study, the nitrogen added as fertilizer and the yield outcomes might be confounded.

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ODSC - Open Data Science

MAY 4, 2023

Amazon’s AI Resume Screening In 2018, Amazon abandoned an AI-powered resume screening tool after it was found to be biased against women. If you are curious to know how your AI/ML models in production might be failing under your noses and how to go about fixing them, be sure to catch my session, “ Why do AI Models go Rogue?

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Defined.ai blog

JANUARY 30, 2023

In January, we publicly unveiled our SaaS platform , which helps data scientists collect, enrich, and structure data to train AI and ML models. 2018’s already been a big year at DefinedCrowd, and the future looks bright. It’s been a big year for us so far. People have noticed. More big news coming. Stay tuned!

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AWS Machine Learning Blog

MAY 31, 2023

In 2018, BERT-large made its debut with its 340 million parameters and innovative transformer architecture, setting the benchmark for performance on NLP tasks. Recent advances in ML have given rise to a new class of models known as foundation models , which have billions of parameters and are trained on massive amounts of data.

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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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Mlearning.ai

MARCH 9, 2023

2018; Sitawarin et al., 2018; Papernot et al., 2018) investigated the vulnerability of deep learning models to adversarial attacks in medical image segmentation tasks, and proposed a method to improve their robustness. 2018; Pang et al., For instance, Xu et al. Another study by Jin et al. Makelov, A., Schmidt, L.,

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