#a borrowed terminology from DEVOps that can be used to manage your model in a receptive fashion using its CI/CD capabilities. Essentially M

[processindustrytspl]

How Seeq enables the Practice of MLOps for Continuous Integration and Development of the Machine Learning Models

Using ML/AI now they have enabled themselves to not only understand the importance of parameters but also to make predictions in real-time and forecast the future values. This helps the industry to manage and continuously improve the process by mitigating operational challenges such as reducing downtime, increasing productivity, improving yields and much more. But, in order to achieve such continuous support for the operations in real-time, the underlying models and techniques also need to be continuously monitored and managed. This brings in the requirement of MLOps, a borrowed terminology from DEVOps that can be used to manage your model in a receptive fashion using its CI/CD capabilities. Essentially MLOps enables you to not only develop your model but also gives you the flexibility to deploy and manage them in the production environment.

#Due to the rapid advancement in technology #the Manufacturing Industry has accepted a wide range of digital solutions that can directly benefit the organization in various ways. One o #increasing productivity #improving yields and much more. But #in order to achieve such continuous support for the operations in real-time #the underlying models and techniques also need to be continuously monitored and managed. This brings in the requirement of MLOps #a borrowed terminology from DEVOps that can be used to manage your model in a receptive fashion using its CI/CD capabilities. Essentially M #Let’s try to add more relevance to it and understand how Seeq can help you to achieve that. #Note: Seeq is a self-service analytics tool that does more than modeling. This article is assuming that the reader is familiar with the bas #Need for Seeq? #Whenever it comes to process data analytics/modeling #visuals become very much important. After all #you believe in what you see #right? #To deliver quick actionable insights #the data needs to get visualized in the processed form which can directly benefit the operations team. The processed form could be the clea #derived data #or even the predicted data #but for making it actionable it needs to be visualized. The solutions should peacefully support and integrate with the culture of Industry. #MLOps in Seeq #For process data analytics models could accept various forms such as first principle #statistical or ML/AI models. For the first two categories #the management and deployment become simple as it is essentially the correlations in the form of equations. Also #it comes with complete transparency #unlike ML/AI models. ML/AI on the other hand is a black-box model #adds a degree of ambiguity and spontaneity to the outcomes #which requires time management and tuning of the model parameters. This could be either due to the data drift or the addition/removal of pa #1.Model Development: #One can make use of Seeq’s DataLab (SDL) module to build and develop the models. SDL is a jupyter-notebook like interface for scripting in #one can use spy.push method to extract the maximum information out of the model using Seeq Workbench and advanced Visualization capabilitie