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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Tableau

DECEMBER 1, 2021

Clustered under visual encoding , we have topics of self-service analysis , authoring , and computer assistance. April 2018), which focused on users who do understand joins and curating federated data sources. Gestalt properties including clusters are salient on scatters. Visual encoding is key to explaining ML models to humans.

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Iguazio

SEPTEMBER 20, 2023

20 Newsgroups A dataset containing roughly 20,000 newsgroup documents spanning a variety of topics, for text classification, text clustering and similar ML applications. million articles from 20,000 news sources across a seven day period in 2017 and 2018. Get the dataset here. Long-Form Content 14. Get the dataset here.

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AWS Machine Learning Blog

JANUARY 13, 2023

It involves training a global machine learning (ML) model from distributed health data held locally at different sites. The eICU data is ideal for developing ML algorithms, decision support tools, and advancing clinical research. Training ML models with a single data point at a time is tedious and time-consuming.

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Mlearning.ai

APRIL 8, 2023

In this article, we’ll look at the evolution of these state-of-the-art (SOTA) models and algorithms, the ML techniques behind them, the people who envisioned them, and the papers that introduced them. 2018) “ Language models are few-shot learners ” by Brown et al. 2020) “GPT-4 Technical report ” by Open AI.

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Flipboard

NOVEMBER 24, 2023

Iris was designed to use machine learning (ML) algorithms to predict the next steps in building a data pipeline. Since joining SnapLogic in 2010, Greg has helped design and implement several key platform features including cluster processing, big data processing, the cloud architecture, and machine learning.

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AWS Machine Learning Blog

JANUARY 17, 2024

SageMaker Studio is an integrated development environment (IDE) that provides a single web-based visual interface where you can access purpose-built tools to perform all machine learning (ML) development steps, from preparing data to building, training, and deploying your ML models. It will show up when you when you choose Train.

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Flipboard

JULY 10, 2023

By using our mathematical notation, the entire training process of the autoencoder can be written as follows: Figure 2 demonstrates the basic architecture of an autoencoder: Figure 2: Architecture of Autoencoder (inspired by Hubens, “Deep Inside: Autoencoders,” Towards Data Science , 2018 ).

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AWS Machine Learning Blog

MAY 2, 2023

JumpStart is a machine learning (ML) hub that can help you accelerate your ML journey. There are a few limitations of using off-the-shelf pre-trained LLMs: They’re usually trained offline, making the model agnostic to the latest information (for example, a chatbot trained from 2011–2018 has no information about COVID-19).

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Mlearning.ai

JANUARY 17, 2024

Traditional AI can recognize, classify, and cluster, but not generate the data it is trained on. The foundations for today’s generative language applications were elaborated in the 1990s ( Hochreiter , Schmidhuber ), and the whole field took off around 2018 ( Radford , Devlin , et al.). Let’s play the comparison game. No, no, no!

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Mlearning.ai

JUNE 8, 2023

machine learning models that learn from almost no training data) Fraud detection/outlier detection Typo detection and all manners of “fuzzy matching” Detecting when ML models go stale (drift) Learning embeddings for your machine learning model An embedding is a mapping from discrete objects, such as words, to vectors of real numbers.

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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., 2018; Sitawarin et al., 2018; Papernot et al., 2018; Pang et al., 2012; Otsu, 1979; Long et al., For instance, Xu et al. Another study by Jin et al.

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Google Research AI blog

FEBRUARY 28, 2023

Adherence to such public health programs is a prevalent challenge, so researchers from Google Research and the Indian Institute of Technology, Madras worked with ARMMAN to design an ML system that alerts healthcare providers about participants at risk of dropping out of the health information program. certainty when used correctly.

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O'Reilly Media

NOVEMBER 28, 2023

The top five responses clustered between 45 and 50%: unexpected outcomes (49%), security vulnerabilities (48%), safety and reliability (46%), fairness, bias, and ethics (46%), and privacy (46%). The next most needed skill is operations for AI and ML (54%). That’s not the same as failure, and 2018 significantly predates generative AI.

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Pickl AI

MAY 16, 2023

Python, Data Mining, Analytics and ML are one of the most preferred skills for a Data Scientist. In fact, these industries majorly employ Data Scientists. Most Preferred Skills With the right skill sets, you have a better probability of success. Passionate about leveraging data to drive business decisions and improve customer experience.

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Snorkel AI

MARCH 21, 2023

Together with David Harvey, an engagement manager focused on scaling deployments and applied R&D at that same firm, they presented the session “Trends in Enterprise ML and the potential impact of Foundation Models” at Snorkel AI’s 2023 Foundation Model Virtual Summit. Our ML protocols need updating in several ways.

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Explosion

MAY 17, 2023

For instance, you could extract a few noisy metrics, such as a general “positivity” sentiment score that you track in a dashboard, while you also produce more nuanced clustering of the posts which are reviewed periodically in more detail. You might want to view the data in a variety of ways.

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PyImageSearch

JULY 3, 2023

Figure 3: Netflix personalized home page view (source: “NETFLIX System Design,” Medium , 2018 ). Machine learning (ML) approaches can be used to learn utility functions by training it on historical data of which home pages have been created for members (i.e., Each row has a title (e.g., user profile, location, query, language, etc.).

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Heartbeat

AUGUST 23, 2023

These algorithms help legal professionals swiftly discover essential information, speed up document review, and assure comprehensive case analysis through approaches such as document clustering and topic modeling. Natural language processing and machine learning as practical toolsets for archival processing.

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Mlearning.ai

FEBRUARY 28, 2023

In 2018–2019, while new car sales were recorded at 3.6 The next step post that would be to cluster different sets of data and see if multiple models should be created for different locations and car types. For this reason, Cars4U was created as a budding tech start-up that aims to find footholds in this market.

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The MLOps Blog

JANUARY 30, 2025

In the seminal 2018 paper BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding , the authors state that they trained the model using Adam with [a] learning rate of 1e-4, =0.9, =0.999, L2 weight decay of 0.01, learning rate warm up over the first 10,000 steps, and linear decay of the learning rate.”

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ML Review

MARCH 5, 2019

Well, actually, you’ll still have to wonder because right now it’s just k-mean cluster colour, but in the future you won’t). Within both embedding pages, the user can choose the number of embeddings to show, how many k-mean clusters to split these into, as well as which embedding type to show. Bojanowski, P., TACL, 5, 135–146.

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