Well first of all its easy to carry as its in my mobile device plus laptop. File sharing is not only secure but also easy to use. giving me all kind of access to google doc, google presentation, data and etc. working on big projects with big teams is being made easy by google drive.
Based on our record, Algorithmia should be more popular than Google Drive. It has been mentiond 5 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
I'm running the latest beta of Ventura and the Google Drive sync app installed from google.com/drive. Source: over 1 year ago
Is Google Drive good for backing up files? Safety of personal Data loss is important, choosing Google Drive as means to Store files and folder is key to preventing loss of Data. Backup files to Google Drive are very useful for to managed personal files and making files easier to share with family and friends. How to use Google Drive for backup. Source: about 2 years ago
To push a model into production, there are additional concerns which the tools in the versioning, deployment and release space aim to solve. This includes obtaining adequate infrastructure to run the model reliably and facilitating easy model release or rollback. Solutions in the MLOps space includes Kubeflow, Pachyderm and Algorithmia. - Source: dev.to / over 2 years ago
And for enterprises that want to do the same with ML you can use algorithmia.com. Source: over 2 years ago
Algorithmia advertises themselves as an MLops platform for data scientists, and they provide an easy way to host models on a scalable REST API. Source: over 2 years ago
Seems similar to https://algorithmia.com. Source: over 2 years ago
Algorithmia.com — Host algorithms for free. Includes free monthly allowance for running algorithms. Now with CLI support. - Source: dev.to / almost 3 years ago
Dropbox - Online Sync and File Sharing
Managed MLflow - Managed MLflow is built on top of MLflow, an open source platform developed by Databricks to help manage the complete Machine Learning lifecycle with enterprise reliability, security, and scale.
Mega - Secure File Storage and collaboration
neptune.ai - Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.
Box - Box offers secure content management and collaboration for individuals, teams and businesses, enabling secure file sharing and access to your files online.
MCenter - Machine Learning Operationalization