Machine Learning Operations (MLOps) is on the rise as a critical technology to help to scale machine learning in the enterprise. According to McKinsey, by 2030, ML could add up to 13 trillion dollars back into the global economy by enabling workers in all sectors to improve their output. Furthermore, MarketWatch indicates that, in 2021, the global MLOps market size will be USD million and it is expected to reach USD million by the end of 2027, with a CAGR during 2021-2027. According to IBM by 2023, 70% of AI workloads will use application containers or be built using a server less programming model, necessitating a DevOps culture. What’s more, according to Algorithmia, 85% of machine learning models never make it to production. For businesses, creating machine learning applications, managing those models and putting them into action is challenging. Different companies, such as DataRobot, have emerged as top machine learning operations tool enablers for the industry to handle these challenges.
Processing, implementing and deploying machine learning models requires specific tools that can solve challenges in the process. The challenge of getting data from aa data to decisions is made more accessible by applying various operations on-device or in the cloud as needed. To do this at scale, businesses need a platform to add support for new ML frameworks through open interfaces. There are several ways to add or remove models and processes.
The leading machine learning operations tools for enterprise are:
Continue reading: https://www.forbes.com/sites/markminevich/2021/09/10/leading-mlops-tools-are-the-next-frontier-of-scaling-ai-in-the-enterprise/?sh=31beaf9263d8
Processing, implementing and deploying machine learning models requires specific tools that can solve challenges in the process. The challenge of getting data from aa data to decisions is made more accessible by applying various operations on-device or in the cloud as needed. To do this at scale, businesses need a platform to add support for new ML frameworks through open interfaces. There are several ways to add or remove models and processes.
The leading machine learning operations tools for enterprise are:
Continue reading: https://www.forbes.com/sites/markminevich/2021/09/10/leading-mlops-tools-are-the-next-frontier-of-scaling-ai-in-the-enterprise/?sh=31beaf9263d8
