Enterprises are using Machine Learning (ML) to transform their business and gain competitive advantage. From healthcare to transportation, supply chain to risk management, machine learning is becoming universal across trades, disrupting markets and reshaping business models.
Organizations need the technology and tools required to build and deploy successful Machine Learning models and operate in an alert way. MLOps is the key to making machine learning projects successful at scale.
The practice of collaboration between data science and IT teams designed to accelerate the entire machine lifecycle across model development, deployment, monitoring, and more.
Microsoft Azure Machine Learning enables companies to fully embrace MLOps practices and truly be able to realize the potential of AI in their business.
Businesses need to apply the consistency and procedures of other software development projects in order to take full advantage of MLOps.
To help organizations with their machine learning journey, GigaOm developed the MLOps vision report that includes best practices for effective implementation and a maturity model.
Maturity is measured through five levels of development across key categories such as strategy, architecture, modeling, processes, and governance. Using the maturity model, enterprises can understand where they are and determine what steps to take to ‘level up’ and achieve business objectives.
To learn more, read the GigaOm report and make machine learning transformation a reality for your business.
If you want to dive deeper into Azure Data Analytics and Machine Learning, come along to our upcoming Azure Data Analytics and Machine Learning Bootcamp & Training which is presented by one of our Senior Data Analytics and Machine Learning experts, Daire Cunningham.