Setting up Storage for a Machine Learning Dataset | Stefan Pfaffel

By Medium - 2021-02-08

Description

Machine learning projects need a scalable storage solution to support classification and learning and training. MongoDB is a popular database choice.

Summary

  • What I Learned Setting up Storage for a Machine Learning Project A journey towards a fast storage solution for a small-scale project It is amazing how far machine learning frameworks and technology, in general, have come and how fast we’re nowadays able to integrate machine learning features into applications.
  • As I’m currently building www.blauspecht.io, a tool dedicated to the creation and scheduling of Twitter content, a.k.a.
  • If the tweets were stored in a database, I could randomly pick one without classification and update each individually.
  • At this moment, I was pleased with what I had achieved.

 

Topics

  1. Backend (0.29)
  2. Database (0.25)
  3. Machine_Learning (0.21)

Similar Articles

Data Science Learning Roadmap for 2021

By freeCodeCamp.org - 2021-01-12

Although nothing really changes but the date, a new year fills everyone with the hope of starting things afresh. If you add in a bit of planning, some well-envisioned goals, and a learning roadmap, yo ...

What is JSON? And why do you need it?

By DEV Community - 2020-12-27

Before going on to the topic JSON, I would like to discuss a simple example because it will be a lot... Tagged with javascript, beginners, tutorial, webdev.

How to put machine learning models into production

By Stack Overflow Blog - 2020-10-12

The goal of building a machine learning model is to solve a problem, and a machine learning model can only do so when it is in production and actively in use by consumers. As such, model deployment is ...