Remove gb-en
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Intl.NumberFormat

David Walsh

format(12345) // 12,345 new Intl.NumberFormat('en-US', { maximumSignificantDigits: 4}).format(1.2345678) format(1.2345678) // 1.235 (Notice the rounding) new Intl.NumberFormat('en-GB', { style: 'currency', currency: 'GBP' }).format(9002.20) Let’s check it out! format(9002.20) // £9,002.20

eCommerce 141
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Curate Custom Content with mediastack

David Walsh

access_key=MY_API_KEY &keywords=Arsenal &countries=gb. access_key=MY_API_KEY &keywords=bitcoin &sources=-foxnews &categories=business &languages=en &sort=popularity &countries=us. Since it’s transfer season in the English Premier League, I could look for news on Arsenal transfers: [link] ?access_key=MY_API_KEY

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AEM Content Fragments: Content Structure

Exadel

The language code must be in one of the following formats: <language-code> The supported language code is a two-letter code as defined by ISO-639-1 (like en). <language-code>_<country-code> Here’s the content structure for them: /en serves as a blueprint. enableReviewers= "false".

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Building a React dashboard to visualize workflow and job events

CircleCI

toLocaleString("en-GB", { month: "long", weekday: "long", day: "numeric", year: "numeric", }); Building dashboard components. To represent dates in a readable format, we can create a utility function. In the utility folder, create a new file called Date.js and add this: export const formatDate = (date) => new Date(date).toLocaleString("en-GB",

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Building a Cross-platform In-app Messaging Orchestration Service

Netflix Tech

The contents of the feedback are not inspected by the UI platform, it is simply a passthrough that is used by the in-app messaging service to implement the orchestration features of the service. { "ttl": 3600, "feedbackType": "cta", "cta": "DISMISS_ALERT", "trackingInfo": { "messageGuid": "786DECAE429EEB029EEE057191675F6764555F12", (..)

Testing 88
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Unleashing the Power of High Throughput OCR with Visual NLP

John Snow Labs

pretrained(checkpointName, "en", "clinical/ocr").setInputCols(["image","regionEmpty"]).setOutputCol("detected_text").setBorderWidth(10).setUseGPU(True).setUseCaching(True).setOutputFormat(OcrOutputFormat.TEXT) pretrained("image_text_detector_opt", "en", "clinical/ocr").setInputCol("image").setOutputCol("detected_regions").setWithRefiner(False)

Metrics 52
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DICOM de-identification at scale in Visual NLP 3/3

John Snow Labs

2023-08-20 14:17:23|426776| + --+ + -+ --+ -+ + For handle big files (2 and more GB) need to use path as input instead of content. pretrained("image_text_detector_v2", "en", "clinical/ocr").setInputCol("image").setOutputCol("regions").setScoreThreshold(0.5).setTextThreshold(0.2).setSizeThreshold(10)