Machine Learning (ML) is a subject to learn as they progress forward with large datasets. Machine Learning has various algorithms, which when exposed to high volumes of data, can self-learn and evolve.
In research, Machine Learning is now moving away from abstraction and applying more in business problem solving with support from Artificial Intelligence and Deep Learning. Big Data is also making way back to mainstream business activities, now machine learning algorithms can use massive loads static and dynamic data to learn and improve for improve performance.
“Updated hardware, memory, storage technologies, more processing power, superior algorithms, and massive data streams will contribute to the success of machine learning powered and artificial intelligence applications. There will be a steady rise in machine learning powered and artificial intelligence application in industry like preventive healthcare sector, banking sector, finance sector, and media sector. In business, that is more automated functions and fewer human checkpoints. Researchers suggest that the Artificial Intelligence and Machine Learning Cloud will increasingly feed on IoT data as sensors and smart applications take over every facet of our daily lives.
The Artificial Intelligence and Machine Learning through Cloud technologies, open standards, and algorithm economy will continue. The growing trend of deploying prebuilt Machine Learning algorithms to enable self-service business Intelligence and analytics is a positive step towards democratization of Machine Learning. This article shows that almost anyone with a laptop and an internet connection can dare to be a Machine Learning expert today provided they have the right mindset.
The demand-supply gap in Artificial Intelligence and Machine Learning skills will continue to rise till academic programs and industry workshops begin to produce a ready workforce. In response to this sharp rise in the demand-supply gap, more enterprises and academic institutions will collaborate to train future Artificial Intelligence and Machine Learning experts. This kind of training will compete with the traditional Artificial Intelligence classroom and will focus more on practical skills rather than on theoretical knowledge.
On one hand, average business will utilize algorithmic models for their operational and customer-facing functions. On the other hand, Machine Learning algorithms will become a market among large and competing enterprises.