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Machine Learning as a Service (MLaaS) Market will witness a CAGR of 49% during the forecast period 2017-2023. Key Players are Microsoft, Amazon Web Services, Google, Inc., and IBM Corporation

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Machine Learning as a Service (MLaaS) Market will witness a CAGR of 49% during the forecast period 2017-2023. Key Players are Microsoft, Amazon Web Services, Google, Inc., and IBM Corporation

MLaaS – Machine learning has become a disruptive trend in the technology industry with computers learning to accomplish tasks without being explicitly programmed. The manufacturing industry is relatively new to the concept of machine learning. Machine learning is well aligned to deal with the complexities of the manufacturing industry. Manufacturers can improve their product quality, ensure supply chain efficiency, reduce time to market, fulfil reliability standards, and thus, enhance their customer base through the application of machine learning.

Machine learning algorithms offer predictive insights at every stage of the production, which can ensure efficiency and accuracy. Problems that earlier took months to be addressed are now being resolved quickly. The predictive failure of equipment is the biggest use case of machine learning in manufacturing. The predictions can be utilized to create predictive maintenance to be done by the service technicians. Certain algorithms can even predict the type of failure that may occur so that correct replacement parts and tools can be brought by the technician for the job.

According to Infoholic Research, Machine Learning as a Service (MLaaS) Market will witness a CAGR of 49% during the forecast period 2017-2023. The market is propelled by certain growth drivers such as the increased application of advanced analytics in manufacturing, high volume of structured and unstructured data, the integration of machine learning with big data and other technologies, the rising importance of predictive and preventive maintenance, and so on. The market growth is curbed to a certain extent by restraining factors such as implementation challenges, the dearth of skilled data scientists, and data inaccessibility and security concerns to name a few.

This article originally appeared on marketwatch.com  To read the full article, click here.

Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously.  To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:

  • Advanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
  • Raw information handling and analytics speed
  • End-to-end business transaction tracking that spans technologies, tiers, and organizations
  • Intuitive, easy-to-use data visualizations and dashboards

If you would like to learn more, click here

Nastel Technologies, a global leader in integration infrastructure (i2) and transaction management for mission-critical applications, helps companies achieve flawless delivery of digital services.

 

Nastel delivers Integration Infrastructure Management (i2M), Monitoring, Tracking, and Analytics to detect anomalies, accelerate decisions, and enable customers to constantly innovate. To answer business-centric questions and provide actionable guidance for decision-makers.
The Nastel Platform delivers:

  • Integration Infrastructure Management (i2M)
  • Predictive and Proactive anomaly detection that virtually eliminates war room scenarios and improves root cause analysis
  • Self-service for DevOps and CI: CD teams to achieve their speed to market goals
  • Advanced reporting and alerting for business, IT, compliance, and security purposes
  • Decision Support (DSS) for business and IT
  • Visualization of end-to-end user experiences through the entire application stack
  • Innovative Machine Learning AI to compare real-time to the historical record and discover and remediate events before they are critical
  • Large scale, high-performance complex event processing that delivers tracing, tracking, and stitching of all forms of machine data
  • And much more

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