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To streamline the process of production, maintenance and monitoring of machine learning models, organizations deploy MLOps. It allows for collaboration between data scientists, IT and developers for smooth communication.
The lifecycle of machine learning comes with complexity, such as data ingest, model deployment, training, monitoring and more, making its implementation complicated. There is also the need for collaboration between data scientists, data engineers, etc. This, in turn, requires rigorous operational synchronization between all touchpoints to work smoothly. This is why organizations have started utilizing MLOps.
MLOps, or Machine Learning Operations with serverless solutions, provide organizations with scalability, lower risk, efficiency, continuous improvement of their lifecycle and automated generation of predictions. This is why organizations deploy MLOps, and its integration is increasing.
The vast benefits provided by MLOps are getting banked on by various organizations in different industries. Here are a few examples:
Online supermarkets are virtual stores that allow customers to shop for groceries and household items over the internet. Customers can browse and purchase products through a website or mobile app and have them delivered to their homes or picked up at a designated location. The use of MLOps in online supermarkets allows for personalization and suggestions of items to consumers. It also predicts demands for goods to avoid understocking or overstocking. Additionally, it optimizes the supply chain to help reduce carbon emissions and preserve the freshness of items. One such online supermarket using MLOps is Ocado.
Leveraging serverless MLOps solutions in the travel and logistics industry can help to streamline customers’ decision-making efficiently. It can also be used to deploy targeted advertisements to an organization’s clients or potential customers. Other great benefits of serverless MLOps are automated call management, personalized customer experience on the site and more.
FinTech companies can use serverless MLOps to mitigate fraudulent transactions by going through millions of transactions quickly yet intricately. This will also assure consumers of secure transactions.
Data is one of the most valuable assets an organization can possess. Due to its vastness, complications can arise and, if not handled correctly, can lead to misinformation. Therefore, the deployment of serverless MLOps solutions streamlines the process of data handling, data preparation, model deployments, and collaboration between data scientists, engineers, etc., and aligns with the organizational goals. Implementation of MLOps should, however, be chosen correctly based on the budget, goals, compatibility with existing tools and more to achieve the desired results.
Naveen is the Founder and CEO of Allerin, a software solutions provider that delivers innovative and agile solutions that enable to automate, inspire and impress. He is a seasoned professional with more than 20 years of experience, with extensive experience in customizing open source products for cost optimizations of large scale IT deployment. He is currently working on Internet of Things solutions with Big Data Analytics. Naveen completed his programming qualifications in various Indian institutes.
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