Azure Machine Learning vs. DigitalOcean

For [a] data scientist require[d] to build a machine learning model, so he/she didn't worry about infrastructure to maintain it.

All kind of feature[s] such as train, build, deploy and monitor the machine learning model available in a single suite.

If someone has [their] own environment for ML studio, so there [it would] not [be] useful for them.

DigitalOcean is perfect for hosting client websites, running marketing tools, and managing media storage with Spaces and CDN. The use of Droplets to quickly launch landing pages or WordPress sites for campaigns is a Godsend. It’s great for fast, cheap, and scalable solutions. But for complex microservices or projects needing strict compliance (like HIPAA), DigitalOcean may not always be the best fit, but that depends heavily on your project.

Incentivized

• User friendliness: This is by far the most user friendly tool I've seen in analytics. You don't need to know how to code at all! Just create a few blocks, connect a few lines and you are capable of running a boosted decision tree with a very high R squared!
• Speed: Azure ML is a cloud based tool, so processing is not made with your computer, making the reliability and speed top notch!
• Cost: If you don't know how to code, this is by far the cheapest machine learning tool out there. I believe it costs less than $15/month. If you know how to code, then R is free.
• Connectivity: It is super easy to embed R or Python codes on Azure ML. So if you want to do more advanced stuff, or use a model that is not yet available on Azure ML, you can simply paste the code on R or Python there!
• Microsoft environment: Many many companies rely on the Microsoft suite. And Azure ML connects perfectly with Excel, CSV and Access files.

Incentivized

• DigitalOcean provides some of the best cost-to-value services available
• The DigitalOcean cloud console is very intuitive and easy to navigate
• DigitalOcean has great support for Docker and other dev ops tools like Terraform.
• DigitalOcean iterates quickly and provides cutting edge features for organizations that want to keep up with the latest and greatest dev ops tooling
• DigitalOcean has a great developer community and numerous support docs/tutorials

Incentivized

• It would be great to have text tips that could ease new users to the platform, especially if an error shows up
• Scenario-based documentation
• Pre-processing of modules that had been previously run. Sometimes they need to be re-run for no apparent reason

Incentivized

• Some products/services available on other Cloud providers aren't available, but they seem to be catching up as they add new products like Managed SQL DBs.
• While they have FreeBSD droplets (VMs), support for *BSD OSs is limited. I.e. the new monitoring agent only works on Linux.
• There are no regions available on South America.
• They don't seem to offer enterprise-level products, even basic ones as Windows Server, MS SQL Server, Oracle products, etc.

Incentivized

I've been very happy with it for my purposes and I plan to continue to use DigitalOcean for the foreseeable future!

Incentivized

Easy and fastest way to develop, test, deploy and monitor the machine learning model.

- Easy to load the data set

-Drag and drop the process of the Machine learning life cycle.

I honestly can't think of an easier way to set up and maintain your own server. Being able to set up a server in minutes and have fully control is awesome. The UX is incredibly intuitive for first-time users as well so there's no reason to be intimidated when it comes to giving DigitalOcean a shot.

Incentivized

Have not found a single second of down time myself. Superior availability.

Incentivized

Very quick response and high performance, you have to fine tune configurations on your machines though.

Incentivized

Support is nonexistent. It's very frustrating to try and find someone to actually talk to. The robot chatbots are just not well trained.

Incentivized

They have always been fast, and the process has been straight-forward. I haven't had to use it enough to be frustrated with it, to be honest, and when I have an issue they fix it. As with all support, I wish it felt more human, but they are doing aces.

Incentivized

Not sure

It is easier to learn, it has a very cost effective license for use, it has native build and created for Azure cloud services, and that makes it perfect when compared against the alternatives. As a Microsoft tool, it has been built to contain many visual features and improved usability even for non-specialist users.

Incentivized

DigitalOcean is an inexpensive product as compared to other products available in the market. The UI is easy and the beginner can also understand the UI with the step by step guide. It provides a lot of custom features and the user needs to pay only for what they are using. Amazon has a complex UI and is on the expensive side. DigitalOcean is simple to use and is easily manageable and the servers can easily be set up without additional cost and such.

Incentivized

Great scalability, you can start with small plans and move up to premium features at a very good price.

Incentivized

• Productivity: Instead of coding and recoding, Azure ML helped my organization to get to meaningful results faster;
• Cost: Azure ML can save hundreds (or even thousands) of dollars for an organization, since the license costs around $15/month per seat.
• Focus on insights and not on statistics: Since running a model is so easy, analysts can focus more on recommendations and insights, rather than statistical details

Incentivized

• Positive - Elastic computer instances make it possible to pay for only for what you need.
• Positive - Competitive pricing - some of the products that DigitalOcean offers are much cheaper than those offered by competitors.
• Negative - Having to go to other cloud computing platforms for more specific, advanced services like Computer Vision optimized services, GPU cloud compute instances, etc...

Incentivized