Gorgonia
readability
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Gorgonia | readability | |
---|---|---|
21 | 51 | |
5,326 | 8,056 | |
1.0% | 7.4% | |
2.8 | 6.3 | |
22 days ago | 2 days ago | |
Go | JavaScript | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Gorgonia
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Machine Learning en GO! 🤯
GitHub - gorgonia/gorgonia: Gorgonia is a library that helps facilitate machine learning in Go.
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Machine Learning
I did end up writing and using a custom library for Random Forest (it's also in AwesomGo) in one real-world project (detecting Alzheimer's and Parkinson's from speech from a mobile app) - https://github.com/malaschitz/randomForest I had better results than the team who used TensorFlow and most importantly I didn't have to use any other technology than Go. For NN's it's probably best to use https://gorgonia.org/ - but it's not exactly a user friendly library. But there is a whole book on it - Hands-On Deep Learning with Go.
- Why isn’t Go used in AI/ML?
- GoLang AI/ML open source projects
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A systematic framework for technical documentation authoring
Perhaps it's a product of French culture, but because Gorgonia[0] has a number of French contributors, this was actually the way we structured our documentation.
But this is the first time I've heard of the name of the framework.
[0]: https://gorgonia.org
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[D] When was the last time you wrote a custom neural net?
Oh it's.Gorgonia
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Most Popular GoLang Frameworks
Website: https://gorgonia.org
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[D] What framework are you using?
I use Gorgonia.
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Why can't Go be popular for machine learning?
What you think about this https://github.com/gorgonia/gorgonia ? I also recall there is something else out there but can't find it at the moment...
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Neural networks in golang
Yep, all of them: https://github.com/gorgonia/gorgonia
readability
- Mozilla: Readability.js
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CSS for readability
I'm working with the Mozilla's readability library https://github.com/mozilla/readability to get the "readable" text from articles and now I want to style the extracted text in a readable way.
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Building a Serverless Reader View with Lambda and Chrome
Do you remember the Firefox Reader View? It's a feature that removes all unnecessary components like buttons, menus, images, and so on, from a website, focusing on the readable content of the page. The library powering this feature is called Readability.js, which is open source.
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Webrecorder: Capture interactive websites and replay them at a later time
I wonder if Firefox "reader mode as a utility" might be a viable alternative for Pinboard like "content oriented" archiving?
https://github.com/mozilla/readability
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Creating an advanced search engine with PostgreSQL
Depending upon the type of content, one might want to look into using the Readability (Browder's reader view) to parse the webpage. It will give you all the useful info without the junk. Then you can put it in the DB as needed.
https://github.com/mozilla/readability
Btw, readability, is also available in few other languages like Kotlin:
https://github.com/dankito/Readability4J
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Seeking a tool or method to convert webpages into Q&A format using NLP
Use Mozilla's Readability to extract that sweet, sweet text content from webpages.
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I built a free prompt managing tool - Knit
Same as above but the ability to grab the entire article text (you can use the Readability library for that: https://github.com/mozilla/readability)
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I need automatic source URLs when I paste any text onto a card or note, like on OneNote.
// Original script // https://gist.github.com/kepano/90c05f162c37cf730abb8ff027987ca3 // Bookmarklet Converter // https://caiorss.github.io/bookmarklet-maker/ // Libraries // https://github.com/mixmark-io/turndown // https://github.com/mozilla/readability javascript: Promise.all([import('https://unpkg.com/[email protected]?module'), import('https://unpkg.com/@tehshrike/[email protected]'), ]).then(async ([{ default: Turndown }, { default: Readability }]) => { /* Optional vault name */ const vault = ""; /* Optional folder name such as "Clippings/" */ const folder = "Clippings/"; /* Optional tags */ const tags = ""; function getSelectionHtml() { var html = ""; if (typeof window.getSelection != "undefined") { var sel = window.getSelection(); if (sel.rangeCount) { var container = document.createElement("div"); for (var i = 0, len = sel.rangeCount; i < len; ++i) { container.appendChild(sel.getRangeAt(i).cloneContents()); } html = container.innerHTML; } } else if (typeof document.selection != "undefined") { if (document.selection.type == "Text") { html = document.selection.createRange().htmlText; } } return html; } const selection = getSelectionHtml(); const { title, byline, content } = new Readability(document.cloneNode(true)).parse(); function getFileName(fileName) { var userAgent = window.navigator.userAgent, platform = window.navigator.platform, windowsPlatforms = ['Win32', 'Win64', 'Windows', 'WinCE']; if (windowsPlatforms.indexOf(platform) !== -1) { fileName = fileName.replace(':', '').replace(/[/\\?%*|"<>]/g, '-'); } else { fileName = fileName.replace(':', '').replace(/\//g, '-').replace(/\\/g, '-'); } return fileName; } const fileName = getFileName(title); if (selection) { var markdownify = selection; } else { var markdownify = content; } if (vault) { var vaultName = '&vault=' + encodeURIComponent(`${vault}`); } else { var vaultName = ''; } const markdownBody = new Turndown({ headingStyle: 'atx', hr: '---', bulletListMarker: '-', codeBlockStyle: 'fenced', emDelimiter: '*', }).turndown(markdownify); var date = new Date(); function convertDate(date) { var yyyy = date.getFullYear().toString(); var mm = (date.getMonth()+1).toString(); var dd = date.getDate().toString(); var mmChars = mm.split(''); var ddChars = dd.split(''); return yyyy + '-' + (mmChars[1]?mm:"0"+mmChars[0]) + '-' + (ddChars[1]?dd:"0"+ddChars[0]); } const today = convertDate(date); // This is the output template // It is similar to an Obsidian core template // except to insert a value we use: ${value} instead of {{value}} const fileContent =`--- type: clipping date_added: ${today} aliases: [] tags: [${tags}] --- author:: ${byline.toString().split('\n')[0].trim()} source:: [${title}](${document.URL}) ${markdownBody} `; // This copies your text to the clipboard navigator.clipboard.writeText(fileContent); // This creates a new document in Obsidian containing your clipping // I commented it out as this isn't what you asked for /* document.location.href = "obsidian://new?" + "file=" + encodeURIComponent(folder + fileName) + "&content=" + encodeURIComponent(fileContent) + vaultName; */ })
- Any js packages to only scrape relevant content from a webpage?
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RSS meets GPT-3
So first part of the task is to "extract the text from URL", and that is achieved by using descendant of https://github.com/mozilla/readability library which can extract text of any URL.
What are some alternatives?
onnx-go - onnx-go gives the ability to import a pre-trained neural network within Go without being linked to a framework or library.
parser - 📜 Extract meaningful content from the chaos of a web page
GoLearn - Machine Learning for Go
koreader - An ebook reader application supporting PDF, DjVu, EPUB, FB2 and many more formats, running on Cervantes, Kindle, Kobo, PocketBook and Android devices
tfgo - Tensorflow + Go, the gopher way
hn-search - Hacker News Search
goml - On-line Machine Learning in Go (and so much more)
readability.php - PHP port of Mozilla's Readability.js
gosseract - Go package for OCR (Optical Character Recognition), by using Tesseract C++ library
rssguard - Feed reader (and podcast player) which supports RSS/ATOM/JSON and many web-based feed services.
bayesian - Naive Bayesian Classification for Golang.
SponsorBlock - Skip YouTube video sponsors (browser extension)