AWS Machine Learning Blog

NOVEMBER 13, 2024

To search against the database, you can use a vector search, which is performed using the k-nearest neighbors (k-NN) algorithm. When you perform a search, the algorithm computes a similarity score between the query vector and the vectors of stored objects using methods such as cosine similarity or Euclidean distance.

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O'Reilly Media

SEPTEMBER 19, 2023

Stage 2: Machine learning models Hadoop could kind of do ML, thanks to third-party tools. But in its early form of a Hadoop-based ML library, Mahout still required data scientists to write in Java. And it (wisely) stuck to implementations of industry-standard algorithms. Those algorithms packaged with scikit-learn?

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AWS Machine Learning Blog

AUGUST 22, 2023

Machine learning (ML) is revolutionizing solutions across industries and driving new forms of insights and intelligence from data. Many ML algorithms train over large datasets, generalizing patterns it finds in the data and inferring results from those patterns as new unseen records are processed. What is federated learning?

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The MLOps Blog

NOVEMBER 30, 2022

These days enterprises are sitting on a pool of data and increasingly employing machine learning and deep learning algorithms to forecast sales, predict customer churn and fraud detection, etc., Data science practitioners experiment with algorithms, data, and hyperparameters to develop a model that generates business insights.

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Mlearning.ai

APRIL 8, 2023

Charting the evolution of SOTA (State-of-the-art) techniques in NLP (Natural Language Processing) over the years, highlighting the key algorithms, influential figures, and groundbreaking papers that have shaped the field. NLP algorithms help computers understand, interpret, and generate natural language.

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AWS Machine Learning Blog

JUNE 21, 2024

Amazon SageMaker JumpStart is a machine learning (ML) hub offering pre-trained models and pre-built solutions. The SageMaker team will manage any version or security updates.For a list of available models, refer to Built-in Algorithms with pre-trained Model Table. Sherry Ding is a senior AI/ML specialist solutions architect at AWS.

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AWS Machine Learning Blog

DECEMBER 14, 2023

Amazon SageMaker Studio offers a broad set of fully managed integrated development environments (IDEs) for machine learning (ML) development, including JupyterLab, Code Editor based on Code-OSS (Visual Studio Code Open Source), and RStudio. It’s attached to a ML compute instance whenever a Space is run.

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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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ODSC - Open Data Science

FEBRUARY 28, 2023

To deliver on their commitment to enhancing human ingenuity, SAS’s ML toolkit focuses on automation and more to provide smarter decision-making. Making Data Observable Bigeye The quality of the data powering your machine learning algorithms should not be a mystery. Cloudera For Cloudera, it’s all about machine learning optimization.

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DataRobot

NOVEMBER 12, 2021

As ML technologists, we must ensure that technology is built in a way that supports a diverse and equitable implementation rather than reinforcing historical mistakes or amplifying bias. AI Implementers: The IT organization that must inherit a model, whether ML Engineers, or more generally ML Ops personnel.

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Mlearning.ai

JUNE 14, 2023

Learning LLMs (Foundational Models) Base Knowledge / Concepts: What is AI, ML and NLP Introduction to ML and AI — MFML Part 1 — YouTube What is NLP (Natural Language Processing)? — YouTube YouTube Introduction to Natural Language Processing (NLP) NLP 2012 Dan Jurafsky and Chris Manning (1.1) Happy learning.

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Iguazio

AUGUST 3, 2023

The contributors recommend using algorithms like Apriori Algorithm to analyze the Market Basket Analysis. While this data is not fresh, it is from 2010-2012, we added it to the list because of the holiday sales data that can be used and could still be relevant. To learn more about ML and retailers, click here.

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Applied Data Science

MARCH 11, 2022

Then, we will look at three recent research projects that gamified existing algorithms by converting them from single-agent to multi-agent: ?️‍♀️ Back in 2012 things were quite different. All the rage was about algorithms for classification. ‍♀️ Data generation as a game —  Generative Adversarial Networks ?

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DataRobot Blog

APRIL 4, 2022

log-linear model or more sophisticated ML models). Bringing Marketing Mix Modeling into the 21st century with ML and Automation. The argument has always been that ML models are too opaque ( black-box ) to be able to produce the level of insights and transparency needed for marketing strategy setting.

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ODSC - Open Data Science

JUNE 8, 2023

Taipy The inspiration for this open-source software for Python developers was the frustration felt by those who were trying, and struggling, to bring AI algorithms to end-users. To deliver on their commitment to enhancing human ingenuity, SAS’s ML toolkit focuses on automation and more to provide smarter decision-making.

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AWS Machine Learning Blog

MAY 5, 2023

In this post, we discuss a machine learning (ML) solution for complex image searches using Amazon Kendra and Amazon Rekognition. Amazon Kendra is an intelligent search service powered by ML, and Amazon Rekognition is an ML service that can identify objects, people, text, scenes, and activities from images or videos.

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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., 2012; Otsu, 1979; Long et al., The MBD algorithm then searches for a subset of nodes (i.e., 2018; Sitawarin et al., 2015; Huang et al., In addition, Zhang et al.

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Heartbeat

OCTOBER 9, 2023

Computer vision algorithms can reconstruct a highly detailed 3D model by photographing objects from different perspectives. But computer vision algorithms can assist us in digitally scanning and preserving these priceless manuscripts. These ground-breaking areas redefine how we connect with and learn from our collective past.

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Pickl AI

APRIL 28, 2023

With more than 650% growth since 2012, Data Science has emerged as one of the most sought-after technologies. With the new developments in this domain, Data Science presents a picture of futuristic technology. At the same time, it has also emerged as one of the highest-paying job profiles.

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Snorkel AI

APRIL 25, 2023

With that said, I’m actually a faculty member at Harvard, and one of my key goals is to help—both academically as well as from an industry perspective—work with MLCommons , which is a nonprofit organization focusing on accelerating benchmarks, datasets, and best practices for ML (machine learning). What’s the silicon substrate?

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Snorkel AI

APRIL 25, 2023

With that said, I’m actually a faculty member at Harvard, and one of my key goals is to help—both academically as well as from an industry perspective—work with MLCommons , which is a nonprofit organization focusing on accelerating benchmarks, datasets, and best practices for ML (machine learning). What’s the silicon substrate?

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Heartbeat

DECEMBER 14, 2023

Williams, Hinton was co-author of a highly cited paper published in 1986 that popularised the backpropagation algorithm for training multi-layer neural networks, although they were not the first to propose the approach. Hinton is viewed as a leading figure in the deep learning community.

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Heartbeat

DECEMBER 8, 2023

This includes cleaning and transforming data, performing calculations, or applying machine learning algorithms. Williams, Hinton was co-author of a highly cited paper published in 1986 that popularised the backpropagation algorithm for training multi-layer neural networks, although they were not the first to propose the approach.

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DrivenData Labs

SEPTEMBER 10, 2024

Advance algorithms and analytic approaches for early prediction of AD/ADRD, with an emphasis on explainability of predictions. Top solvers from Phase 2 demonstrate algorithmic approaches on diverse datasets and share their results at an innovation event. Paola Ruíz Puente is a Biomedical Engineer amd the AI/ML manager at IGC Pharma.

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DrivenData Labs

MAY 1, 2025

Advance algorithms and analytic approaches for early prediction of AD/ADRD, with an emphasis on explainability of predictions. Top solvers from Phase 2 demonstrate algorithmic approaches on diverse datasets and share their results at an innovation event. changes between 2003 and 2012). Phase 2 [Build IT!]

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O'Reilly Media

APRIL 23, 2024

Why is it that Amazon, which has positioned itself as “the most customer-centric company on the planet,” now lards its search results with advertisements, placing them ahead of the customer-centric results chosen by the company’s organic search algorithms, which prioritize a combination of low price, high customer ratings, and other similar factors?

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IBM Journey to AI blog

JULY 19, 2023

in 10 years, from 2012 to 2022. In a nod to the growing usage of Machine learning in life sciences, FDA has now cleared more than 500 medical algorithms that are commercially available in the United States. More than half of algorithms on the U.S. Business Value As per FAERS database , the number of reported AEs has grown 2.5x

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AWS Machine Learning Blog

OCTOBER 24, 2024

It’s important to select the most suitable k-NN algorithm and parameters for your specific needs, as detailed in this post. For additional details, see Choose the k-NN algorithm for your billion-scale use case with OpenSearch. It requires IAM permission for OpenSearch Service Serverless.

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AWS Machine Learning Blog

OCTOBER 11, 2024

This makes it a popular option for a vector database when using Amazon Bedrock Knowledge Bases, because it makes it straightforward to build modern machine learning (ML) augmented search experiences and generative AI applications without having to manage the underlying vector database infrastructure.

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Mlearning.ai

FEBRUARY 10, 2023

Neural networks are a type of machine learning algorithm that are used for tasks such as pattern recognition, classification, and prediction. How are neural networks like databases? As of today, neural networks and databases are two different types of systems that are used for different purposes.

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