blackjack-basic-strategy
HANDSONTABLE
blackjack-basic-strategy | HANDSONTABLE | |
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23 | 17 | |
26 | 19,093 | |
- | 0.9% | |
2.0 | 9.6 | |
about 1 year ago | 5 days ago | |
JavaScript | JavaScript | |
MIT License | 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.
blackjack-basic-strategy
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Show HN: Pip install inference, open source computer vision deployment
It’s an easy to use inference server for computer vision models.
The end result is a Docker container that serves a standardized API as a microservice that your application uses to get predictions from computer vision models (though there is also a native Python interface).
It’s backed by a bunch of component pieces:
* a server (so you don’t have to reimplement things like image processing & prediction visualization on every project)
* standardized APIs for computer vision tasks (so switching out the model weights and architecture can be done independently of your application code)
* model architecture implementations (which implement the tensor parsing glue between images & predictions) for supervised models that you've fine-tuned to perform custom tasks
* foundation model implementations (like CLIP & SAM) that tend to chain well with fine-tuned models
* reusable utils to make adding support for new models easier
* a model registry (so your code can be independent from your model weights & you don't have to re-build and re-deploy every time you want to iterate on your model weights)
* data management integrations (so you can collect more images of edge cases to improve your dataset & model the more it sees in the wild)
* ecosystem (there are tens of thousands of fine-tuned models shared by users that you can use off the shelf via Roboflow Universe[1])
Additionally, since it's focused specifically on computer vision, it has specific CV-focused features (like direct camera stream input) and makes some different tradeoffs than other more general ML solutions (namely, optimized for small-fast models that run at the edge & need support for running on many different devices like NVIDIA Jetsons and Raspberry Pis in addition to beefy cloud servers).
[1] https://universe.roboflow.com
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Open discussion and useful links people trying to do Object Detection
* Most of the time I find Roboflow extremely handy, I used it to merge datasets, augmentate, read tutorials and that kind of thing. Basically you just create your dataset with roboflow and focus on other aspects.
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TensorFlow Datasets (TFDS): a collection of ready-to-use datasets
For computer vision, there are 100k+ open source classification, object detection, and segmentation datasets available on Roboflow Universe: https://universe.roboflow.com
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Please suggest resources to learn how to work with pre-trained CV models
Solid website and app overall for learning more about computer vision, discovering datasets, and keeping up with advancements in the field: * https://roboflow.com/learn * https://universe.roboflow.com (datasets) | https://blog.roboflow.com/computer-vision-datasets-and-apis/ * https://blog.roboflow.com
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Suggestion for identification problem with shipping labels?
If you're lacking training images, you can also use [Roboflow Universe](https://universe.roboflow.com) to obtain them (over 100 million labeled images available)
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Ask HN: Who is hiring? (November 2022)
Roboflow | Multiple Roles | Full-time (Remote) | https://roboflow.com/careers
Roboflow is the fastest way to use computer vision in production. We help developers give their software the sense of sight. Our end-to-end platform[1] provides tooling for image collection, annotation, dataset exploration and curation, training, and deployment.
Over 100k engineers (including engineers from 2/3 Fortune 100 companies) build with Roboflow. And we now host the largest collection[2] of open source computer vision datasets and pre-trained models[3].
We have several openings available, but are primarily looking for strong technical generalists who want to help us democratize computer vision and like to wear many hats and have an outsized impact. (We especially love hiring past and future founders.)
We're hiring 3 full-stack engineers this quarter and we're also looking for an infrastructure engineer with Elasticsearch experience.
[1]: https://docs.roboflow.com
[2]: https://blog.roboflow.com/computer-vision-datasets-and-apis/
[3]: https://universe.roboflow.com
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When annotating an image, if a collection of an entity changes the nature of the entity, do you label them collectively or separately?
Based on what I do/use when I prepare models: A good framework for creating and improving this dataset faster is to use Roboflow Universe and search “flowers” and “bouquets of flowers” in the search bar (it’s like Google Images for CV Datasets). You can search images by subject, or metadata, and clone them directly into a free public workspace (they house up to 10k images without charge). * https://universe.roboflow.com/ * https://universe.roboflow.com/search?q=flowers * https://universe.roboflow.com/search?q=bouqets
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Need help on finding an area where machine learning is applicable on day-to-day life but not implemented already
Lots of ideas will come to mind if you look and search through open source datasets: https://universe.roboflow.com/
- Ask HN: Any good self-hosted image recognition software?
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SAAS for object detection?
Open source datasets: https://universe.roboflow.com/ Model training: https://docs.roboflow.com/train Model deployment: https://docs.roboflow.com/inference/hosted-api
HANDSONTABLE
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MUI Datagrid resizable columns (free solution)
handsontable
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Ideas for displaying Excel files in browser
There is also https://handsontable.com/
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What’s new in Handsontable Data Grid: November 2022
We are currently working on translating three new UI labels into 18 different languages. Can you help us out with it?
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Recommendation on stack for a spreadsheet-like product
https://handsontable.com/ This is the best commercial library you can just buy and put it in your product.
- What Web/Frontend framework has Virtual ListView, Splitter, scrollable TreeView components?
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[AskJS] Is there a good table js library?
I've always liked https://handsontable.com/ but I'm not sure what the licensing is for something other than a personal project.
- Ask HN: Who is hiring? (November 2022)
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What’s new in Handsontable Data Grid: September 2022
trimWhitespace option can finally be used in columns and cells #7387,
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What’s new in Handsontable Data Grid: July 2022
All our packages are on npm, so depending on the framework you use, you can install it as follows:
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Top JavaScript Spreadsheet Components for Data Management Apps
Handsontable is primarily known as a JavaScript grid library for business apps but the decision to include it in this article is not accidental. Although this tool doesn't offer as many text formatting options as Excel, it includes quite a lot of features for manipulating data typical of spreadsheets. The list of the most widely used Handsontable features includes operations on rows & columns (moving, hiding, resizing, freezing), CRUD actions, non-contiguous selection, data validation, export to file, and merging cells. You can also take advantage of more advanced capabilities such as multi-column sorting, data summaries, trimming rows, and nested headers.
What are some alternatives?
uxp-photoshop-plugin-samples - UXP Plugin samples for Photoshop 22 and higher.
ag-Grid - The best JavaScript Data Table for building Enterprise Applications. Supports React / Angular / Vue / Plain JavaScript.
wallet - The official repository for the Valora mobile cryptocurrency wallet.
SheetJS js-xlsx - 📗 SheetJS Spreadsheet Data Toolkit -- New home https://git.sheetjs.com/SheetJS/sheetjs
process-google-dataset - Process Google Dataset is a tool to download and process images for neural networks from a Google Image Search using a Chrome extension and a simple Python code.
Jspreadsheet CE - Jspreadsheet is a lightweight vanilla javascript plugin to create amazing web-based interactive tables and spreadsheets compatible with other spreadsheet software.
rollup-react-example - An example React application using Rollup with ES modules, dynamic imports, Service Workers, and Flow.
Luckysheet - Luckysheet is an online spreadsheet like excel that is powerful, simple to configure, and completely open source.
edenai-javascript - The best AI engines in one API: vision, text, speech, translation, OCR, machine learning, etc. SDK and examples for JavaScript developers.
React Data Grid - Feature-rich and customizable data grid React component
Speed-Coding-Games-in-JavaScript - Games Repository from Speed Coding channel
react-excel-renderer - A react library to render and display excel sheets on webpage