Wondering if Create ML has a Sound Classifier as well.. Will make it easy to classify different bird's sounds or to identify music notes from different instruments.. something like piano/guitar notes classifier

This is a nice introduction to sound classification with Create ML:

https://developer.apple.com/videos/play/wwdc2019/425/

It does. Not sure how well it works though.

https://developer.apple.com/documentation/createml

Great product!! Super simple to onboard, cheap and very useful. What service are you using from sending Emails and Text notification?

Thanks uberneo! I'm using Sendgrid for emails (looking to switch to something with high deliverability, high trust, and easy analytics if you have any suggestions!) and Twilio for texts (super friendly SDKs).

Postmark is great for sending transactional email with high deliverability.

With that sliding keyboard it reminds me of Nokia N900. I still have one of those .. might dust it off so !!

Simple example of MicroPayments using Bitcoin Lightning Network - https://twitter.com/micropaylink/status/1231255048509952002?...

few more similar (python based) command line options for Firefox Send - https://github.com/nneonneo/ffsend & https://github.com/ehuggett/send-cli

Would be great to have something like curl -X POST @myFilePath "https://api.send.firefox.com"

This looks really great with such a simple UI.last year I tried to do a realtime sentiment analysis on twitter messages using TextBlob.It was fast but not very accurate. Can you suggest any other library which might works fast enough on realtime messages.

For inference speed I recommend a Naive Bayes model. I've tried this on Twitter messages and got near ~90% accuracy with 3-class (positive, negative, neutral).

The easiest library to do that would probably be scikit-learn with their ComplementNB class: https://scikit-learn.org/stable/modules/generated/sklearn.na...

For the data you can use the SemEval 2017 Task4-A dataset (around ~10K labeled tweets): https://github.com/cbaziotis/datastories-semeval2017-task4/t...

The issue is more obvious when rounding something like 0.5, which, due to lack of precision can become either 0 or 1.

Shameless plug: use https://www.npmjs.com/package/bigint-money

Hey , just check your product , its looks great!! good job. Wondering from how long you have been storing this data and have you using the Public API from each exchange to fetch all this data?

Hi, thanks! It took me over six months to finish it and as always with my ideas seems like market for it is too small, at least currently.

Data is available since 2019-03-30 for majority of the supported exchanges. Yes it's all from public APIs.

I can imagine , as a tech stack , you must be using ccxt , nodejs and some Timeseries database ? Also what all distinct "channels" you are saving ?

No it's all custom stuff written from scratch, some in .NET Core, some in JavaScript (Cloudflare workers, Node.js client libs). I'm saving to flat files on Google Cloud Storage and Wasabi (S3 compatible alternative), given TBs of data it's much cheaper. Filtering is being done on demand. Regarding channels that heavily depends on exchange, you can use https://tardis.dev/api/v1/exchanges/:exchange API to get the list (eg. https://tardis.dev/api/v1/exchanges/bitmex)

This reminds me of the movie "The Hummingbird Project" - https://www.imdb.com/title/tt6866224/ , where speed matters in all Financial transactions and even a 1ms matters in the game

I can see that there is no variable of "fees" which usually applies even on a LIMIT order. For example Coinbase Pro has Maker fees of 0.15%. Ideally this fees should be added to BUY order and subtracted from SELL order, as that will actually cost you.