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Still, using the bulky immovable hardware to run your models?
Is your infrastructure costs giving you a hard time in your development?
It is time to switch to the cloud.
The platforms provide a web-based interface with the ability to scale up and scale down your compute as needed.
The following platforms are powered with cloud infrastructure, which is deemed to be resilient and agile.
Amazon Sagemaker
Amazon Sagemakeris a platform dedicated to the machine learning domain.
Amazon Sagemaker provides you with a scalable cloud computing platform to build, train, and deploymachine learning modelsquickly.
Major benefits of using Amazon Sagemaker are:
Learning Sagemakeris easy.
It offers a grand suite of pre-built examples and startup codes, to begin with.
These coding examples help the developer to get off the feet quickly.
It provides a developer with an interface that is powered with a backend dedicated to machine learning.
The backend is pre-installed with the majority of the required libraries for machine learning.
IBM Watson Studio
IBM Watson Studiois an excellent platform for collaborative development.
Some of the benefits it offers.
It is a premium platform with over a hundred open-source libraries pre-configured for use.
It has a self-learning and analyzing data modeling algorithm.
This is made possible with absolutely no coding at your end.
This suite is built with the majority of the necessary algorithms coded in.
This allows enterprise developers to get a jump start for their applications and build rapidly around it.
The image above depicts how vast the suite is spread.
Some of the benefits are as below.
Conclusion
Machine Learning and AI are covering the world with its impactful outcomes.
The technologies are here to stay and evolve with time.
The products utilizing these technologies are resource hungry and need sufficient power to develop as well as deploy them.
This makes it easier to transition between platforms and keep thedevelopment goingwithout any major hiccups.
