According to research done by Tech pro, the companies having experience in AI or Machine learning is only 28%. The demand and future scope for machine learning are bright and productive oriented. Machine Learning is one of the emerging technologies which is an application of Artificial Intelligence(AI) that provides systems to automatically learn and upgrade from experience without being precisely programmed. So lets get to know is machine learning the future of Cloud Computing.
Machine learning expands the scope of cloud computing by facilitating centralized data storage, simplifying data management. Meanwhile, cloud computing serves as the foundation for various emerging technologies.
Companies like Amazon, Google, and Microsoft adopt Machine Learning technology to make their cloud services more convenient than one another. Google, a leading search engine, views machine learning and deep analytics as the future of cloud computing. It prioritizes implementing machine learning for faster big data prediction and enhanced search engine algorithms.
Before understanding the scope of machine learning in cloud computing, let us first understand a few benefits of machine learning.
Benefits of Machine Learning:
- It helps in simplifying the time-intensive documentation in data entry.
- It helps in streamlining product marketing and supports accurate sales forecasts.
- Assists in accurate medical predictions and diagnosis.
- Ease to detect spam
- Increase the effectiveness of predictive maintenance in the manufacturing industry.
As we have discussed the benefits of machine learning, let us now dive into the reasons for machine learning in cloud computing.
Reasons for Machine Learning in Cloud Computing:
Ubiquity:
Earlier machine learning systems were costlier and more complex to be handled by an enterprise. But cloud computing technology has changed the synopsis, making machine learning more practical and applicable than before. Machine learning is pivotal in leveraging big data to prevent fraudulent transactions, decrease customer churn, and provide product recommendations.
Scalability and Adjustability:
Machine Learning systems are highly scalable and adjustable when it comes to accessing and storing data. Interestingly, the cloud platform becomes reasonable as we make use of it for storing huge amounts of data, and the same applies to machine learning systems.
Statistics:
Normally, large databases comprise complex statistics, and it isn’t easy to analyze such a huge dataset. So, machine learning helps in providing different data analysis reports and provides the statistics that are simpler and easy to understand.
Variation:
The cloud is ideal for integrating machine learning workloads due to its flexibility in data access and storage. This variability supports entrepreneurs in utilizing machine learning for business operations, saving on storage space and costs.
Conclusion:
In the future, the storage and retrieval of vast amounts of data may become necessary, a task facilitated by Machine Learning. Its capabilities in data analysis and access make the cloud more flexible and scalable, affirming machine learning as the future of cloud computing.
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