blackjack-basic-strategy VS Alpaca-API

Roboflow Universe. Image source: Roboflow Universe

FWIW you can use roboflow models on-device as well. detect.roboflow.com is just a hosted version of our inference server (if you run the docker somewhere you can swap out that URL for localhost or wherever your self-hosted one is running). Behind the scenes it’s an http interface for our inference[1] Python package which you can run natively if your app is in Python as well.

Pi inference is pretty slow (probably ~1 fps without an accelerator). Usually folks are using CUDA acceleration with a Jetson for these types of projects if they want to run faster locally.

Some benefits are that there are over 100k pre-trained models others have already published to Roboflow Universe[2] you can start from, supports many of the latest SOTA models (with an extensive library[3] of custom training notebooks), and tight integration with the dataset/annotation tools that are at the core of Roboflow for creating custom models, and good support for common downstream tasks via supervision[4].

[1] https://github.com/roboflow/inference

[2] https://universe.roboflow.com

[3] https://github.com/roboflow/notebooks

[4] https://github.com/roboflow/supervision

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

* 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.

For computer vision, there are 100k+ open source classification, object detection, and segmentation datasets available on Roboflow Universe: https://universe.roboflow.com

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

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)

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

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

Lots of ideas will come to mind if you look and search through open source datasets: https://universe.roboflow.com/

I’ve got a soft spot for Alpaca. I really do. They make it stupidly easy to open an account, paper trade, and even integrate with some neat tools.

Alpaca.Markets | REMOTE (EU or US, EU preferred) | Software Engineer, Senior Software Engineer | varies on location

Alpaca [0] offers brokerage APIs that let you (and your customers) trade various financial instruments all around the world. I'm helping Alpaca set up a new team focused on crypto perpetual futures — they're a really elegant abstraction for trading with varying leverage, and most crypto traders prefer to trade perps rather than spot.

We're looking for candidates who like ~greenfield engineering (brand new domain within Alpaca, some integration with the legacy systems is necessary but a lot of what we're doing is new) and actually writing code. Our hiring philosophy is to bring in the right people, pay them well, and give everyone meaningful work to do.

Alpaca as a whole is about 50 engineers. We're primarily golang microservices on top of kubernetes, but we'll use whatever tools are best to get the job done and satisfy our customers. To get an idea for the kind of work we do, check out what we shipped in 2024 [1].

Apply here: https://boards.greenhouse.io/alpaca/jobs/5319640004

Any questions, feel free to email me peter.downs @ alpaca.markets.

[0]: https://alpaca.markets/

[1]: https://alpaca.markets/blog/alpaca-2024-year-in-review/

You can continuously roll options contracts. I don't know if any broker offers an order type to roll automatically; otherwise I really like Alpaca's API (https://alpaca.markets/)

Is there anyone using Alpaca for long term and passive investing? I am neither a US nor Europe residence, so it is pretty hard to find a decent broker. I came across alpaca.market https://alpaca.markets/ and noticed that there is zero comission for buying and selling stocks. I know that it has pretty good API especially for developers and day traders, but i am particularly interested in long term passive investing, and not interesting in day trading at all. Is it goog for long term passive investing (buying and holding etfs)?

No worries at all! https://alpaca.markets/ is another route for market data. Real time data is cheaper but it is lacking technical analysis. We used to use it and it's pretty good.

Alpaca: https://alpaca.markets/

Access to historical data from Alpaca and Yahoo Finance, or from your own data provider.

I have been looking at https://alpaca.markets/ and wanted to use it to test out some of my API based trading.

What guarantees or structures are in place to make sure it doesn't end up like FTX?

Market data is an easier one to answer. We currently use https://alpaca.markets/ and they're pretty good, but we're also looking at https://polygon.io/ as they're the industry leader (but also 2k per month for what we require).

I'm trying to make an HTTPS request with an ESP32 to this website alpaca.markets. I have the CA cert and I'm using WiFiClientSecure.h. Here's my code, main.cpp is underneath all that.