How to Deploy a Tensorflow Machine Learning Model to Live Production
Complete end to end demonstration. Plus know that this guys is probably one of the best ML tutors I have come across on Youtube
Complete video description:
Once we’ve trained a model, we need a way of deploying it to a server so we can use it as a web or mobile app! We’re going to use the Tensorflow Serving library to help us run a model on a server that we can then make HTTP requests to for data. We’ll have the user upload an image and it will return a classification for that image.
Bryan that guy is “educator” not a (quant) “trader”
As for “quant/math” and trading https://evoeftimov.wordpress.com/2016/07/30/trading-and-math/
Trading is a Zero Sum Game – in order for you to win somebody else has to lose.
To all pure quant chaps out there (or the general public being fed stories about the “magical quants”) – If you want to treat trading as a “physical system” you have to model / or assume the planets/molecules have their own independent brains / will ….
Use math as a tool helping you to PLAY the game. Don’t try to “solve” the market as (rigid) math equation/model.
“(Pure) Mathematical Models” are (can be) different from “Algorithms”, although the difference can be blurred. Algorithms (algorithmic trading) on the other hand are not very different from “(discretionary) trading knowledge”, which can be codified.
Out of all the things to learn when it comes to automated trading is math models. It is so confusing I’m nowhere close to understanding it but thankfully there was an article to help introduce this for any newbie like me.
As I keep doing these LIVE lessons for my Quant Elite members, I completed another important step to showcase how you can use a long/short trading pair as an optimal trading opportunity. You want to generate as many ideas as possible but with automation, you can quickly determine the optimal market entries and exits for position management.
As you know, my Algo Trading Course series covers a lot of this via pair trading or arbitrage in the world of equities. I have been doing this since February every Tuesday to showcase the Python source code.