blackjack-basic-strategy
open-data
blackjack-basic-strategy | open-data | |
---|---|---|
23 | 25 | |
26 | 2,213 | |
- | 0.9% | |
2.0 | 0.0 | |
about 1 year ago | 9 days ago | |
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
-
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
-
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.
-
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
-
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
-
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)
-
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
-
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
-
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?
-
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
open-data
- How to practice data analytics skills
-
[OptaJoe]2009 - Arsenal have won a Premier League game they were losing at half-time outside of London for the first time since December 2009 (2-1 at Liverpool). Temperament.
You can check statsbomb open data but you will to preprocess it from json to sql. They have great course and articles about analyzing the data. Another good reading is awasome-football . They provide list of resources to get data. But the most comprehensive and recommended resources eddwebster's guide. He worked for city football group and his repository updated frequently.
-
Enzo Fernández Progressive Passes - World Cup 2022
I tried visualising Enzo's progressive passes in each of his world cup matches. I used the data available on StatsBomb for this.
-
Football (soccer) player statistics - looking for free databases
https://www.football-data.org/coverage https://datahub.io/collections/football https://github.com/statsbomb/open-data https://www.kaggle.com/datasets/hugomathien/soccer https://www.kaggle.com/datasets/martj42/international-football-results-from-1872-to-2017 https://www.kaggle.com/datasets/secareanualin/football-events https://www.kaggle.com/datasets/adityadesai13/european-football-database-20192020 https://www.kaggle.com/datasets/vivovinco/20212022-football-player-stats https://www.kaggle.com/datasets/antoinekrajnc/soccer-players-statistics
-
Ask HN: Who is hiring? (September 2022)
StatsBomb | Multiple roles | REMOTE, or Bath (UK), or Cairo (Egypt)
StatsBomb is a sports analytics startup, covering football (both the soccer and American varieties) and soon basketball. We sell data products as well as analysis tools to sports, media and gambling organisations, with a tech pipeline that includes computer vision, machine learning, stream processing, and web-based dataviz. We count many of the biggest names in football as customers, and your work will have a direct impact on our ability to deliver insights to those customers, driving success on the field.
We're hiring software engineers of various stripes (data pipeline roles with Python and Clojure, full-stack web dev roles with JavaScript) and more besides. We're fully remote, but have offices in Bath, UK and Cairo, Egypt for those that want them. We organise regular team days and also run our own industry-leading conference each year.
- Apply at: https://statsbomb.com/careers
If you'd like to find out more about football analytics:
- Play with our open data: https://github.com/statsbomb/open-data
- Read our articles: https://statsbomb.com/articles/
- Browse our conference videos: https://www.youtube.com/channel/UCmZ2ArreL9muPvH49Gaw0Bw
-
[OC] Football Wind ⚽️💨 A wind map visualisation of a typical football game. Each particle is following a force field built from the aggregation of 882,536 passes from 890 matches played in various major leagues/cups.
The data source providing all the passes is from StatBomb
-
🏆 TAA vs the u23 world: progressive passes/90 & xA/90
If you're familiar with GitHub and JSON then https://github.com/statsbomb/open-data looks decent.
-
Looking for football (soccer) granular datasets
The company StatsBomb, which specializes in football analytics, has made a lot of their data available for public use here: https://github.com/statsbomb/open-data I’ve been playing with it recently and I’ve found it to be pretty great.
-
[OC] Lionel Messi's shots and goals with Barcelona during his record-breaking 2011/2012 season, compared to his attempts in the 2014 and 2018 World Cups with Argentina
Messi has routinely been one of the best performers in European soccer, including his record-breaking 2011-2012 season in the Spanish league (“La Liga”) with Barcelona, where he set the record for most goals in a season. Unfortunately, success with the Argentina national team has frequently eluded him, finishing as a “runner-up” in the World Cup once and in the Copa America 3 times, before finally winning the Copa America in 2021. Critics often point to his difficulties with his national team as a fatal flaw. I was interested in how his scoring opportunities during arguably his best performance at Barcelona compared to his chances made with Argentina. The data suggests that he is regularly shooting from further away from goal when playing with Argentina when compared to his best performance with Barcelona, which could be a result of a number of factors (different team tactics, difficulty getting up the field, increasing age, less familiarity with teammates, etc.). Data: 2011/2012 La Liga season and World Cup 2018 data were collected from the very nice, public datasets provided by StatsBomb at https://github.com/statsbomb/open-data. The World Cup 2014 data was a bit more difficult to find, but was scraped from the Huffington Post . The StatsBomb data has a ton of great stats to dig into, but because the Huffington Post data had less detail, I wasn't able to go into all of it with just this plot.
-
xG stats for individual shots.
I think Statsbomb has a free API you can use on Github if you request access. https://github.com/statsbomb/open-data
What are some alternatives?
uxp-photoshop-plugin-samples - UXP Plugin samples for Photoshop 22 and higher.
opendata - SkillCorner Open Data with 9 matches of broadcast tracking data.
wallet - The official repository for the Valora mobile cryptocurrency wallet.
geometry-api-java - The Esri Geometry API for Java enables developers to write custom applications for analysis of spatial data. This API is used in the Esri GIS Tools for Hadoop and other 3rd-party data processing solutions.
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.
sample-data - Metrica Sports sample tracking and event data
rollup-react-example - An example React application using Rollup with ES modules, dynamic imports, Service Workers, and Flow.
football_analytics - 📊⚽ A collection of football analytics projects, data, and analysis by Edd Webster (@eddwebster), including a curated list of publicly available resources published by the football analytics community.
edenai-javascript - The best AI engines in one API: vision, text, speech, translation, OCR, machine learning, etc. SDK and examples for JavaScript developers.
nba-movement-data - SportVU movement tracking data.
Speed-Coding-Games-in-JavaScript - Games Repository from Speed Coding channel
geomesa - GeoMesa is a suite of tools for working with big geo-spatial data in a distributed fashion.