Avatar of jollyredflames
Technical Lead at DreamTune·

(2/3) Numpy: This is a package for scientific computing in python. Vectorised code from this library also makes this very efficient. This is an absolutely essential library for machine learning and will help us develop our models efficiently. SciKit-Learn, our machine learning library of choice, uses Numpy extensively and therefore it has to be used by us.

SciKit-Learn: SciKit-Learn is a machine learning library in python. It includes models for regression, classification, clustering, SVM’s, forests, etc. We have chosen this because of all the types of models it offers and the ease with which they can be integrated with our software.

Stripe: POS system of choice with direct integration to all major forms of payment. By using stripe, we can worry less about payment security as they are innovators in the industry and are dedicated to making POS reliable, fast, and scalable.

Firebase: Direct integration into Python makes this NoSQL database a perfect choice. Search is fast and uses an indexing method similar to Google allowing for low latency. Also has the benefit of allowing context casting to remodel JSON data into workable python objects easily.

Heroku: Heroku integrates really well with GitHub and makes the process of deploying our web app extremely easy. After setting up Heroku on our GitHub project, a simple push to it’s master branch deploys the updates. It’s really simple to set up and uses and it is absolutely free. Furthermore, it makes the web app accessible to everyone instead of deploying it locally which is a huge plus.

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Avatar of Sarthak Saxena

Sarthak Saxena

Technical Lead at DreamTune