Machine learning (ML) infrastructure is becoming a critical issue in many companies, as deep learning models become more and more popular in business applications. However, to build an infrastructure for machine learning in a production context, there are certain functions and considerations needed to be taken into account.
- Design Your Machine Learning Infrastructure for Production Purposes
When you start to build machine learning infrastructure, it is necessary to design it according to your production’s needs, because academic machine learning is different from industrial machine learning. Industrial machine learning will not be able to wait for perfect accuracy because the iteration of the model needs to be deployed to production.
- Develop the Critical Elements of Setting up Production Machine Learning
You should make sure that the capabilities and critical elements for building production machine learning are in place. Your design should also consider the need to accelerate machine learning development once your machine learning model is deployed to production. And the infrastructure would have no significant technical debt. Otherwise, this could retard its deployment to production and integration into your existing technology stack.
- Optimize Utilization of Machine Learning Server
You should track how much of your server capacity is being wasted because of inappropriate or inefficient utilization. And data scientists can use the data and information to learn how to improve the way they use the machine learning servers. They can find more effective and efficient methods to use server capacity and other resources.
- Help Data Scientists Focus on Development
Data scientists are often preoccupied with non-data science tasks. You need have a sound resource management system to help operate and maintain machine learning infrastructure for production.
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Rani Tarek jarkas a senior-level software engineer with global experience demonstrating consistent success and effectiveness in website, business, and project delivery skills. Working and collaborating with specialist Advertising & Brand Agencies in the Middle East and Europe for over ten years
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