Every organization wants to execute machine learning on a bigger scale and for less cost. Cloud service providers will proceed to compete to drive down the costs and increase the capacity of machine learning systems. We've seen Google's cloud services produce from storage to include a set of machine learning tools across language, speech, and images. They have gone so far as to build custom hardware(the tensor processing unit) for assisting users to train their machine learning systems quickly. Amazon's AWS and Azure have similar offerings. The end outcome is the democratization of large scale machine learning tools and infrastructure.
Every research team wants to do machine learning with fewer data. Acquiring data is expensive and time-consuming. And because of bigger, quicker, cheaper machine learning, which is more precise with less data, we will see the number of applications and use cases of machine learning continue to rise across all sectors.
If you want to know more about Machine Learning then do check out the following blog by Intellipaat:
And if you want a hands-on experience then do refer the following video tutorial:
If you are a beginner and want to know more about the aforementioned domain, you can pursue a Machine Learning Training from Intellipaat.