A 9-Step Recipe for Successful Machine Learning

Successful artificial intelligence (AI) and machine learning (ML) initiatives bring value to the entire organization by delivering insights to the right person or system at the right time within the right context. But many organizations are unable to do this because they are too focused on algorithms. Data science is more than neural networks and deep learning! Organizations need to instead leverage people, processes, and technology to infuse AI and ML into business processes.

Operationalize AI & ML

It’s kind of like making homemade bread. It sounds simple, only four ingredients: flour, water, yeast, and a bit of salt. But if you don’t follow the recipe or forget one of the critical ingredients, you end up with inedible bread. AI and ML initiatives require the same level of care to get it just right. Read this whitepaper for an easy-to-follow recipe to help you operationalize AI and ML and turn your data science home kitchen into a fully-functional bakery.

Read this whitepaper to improve each aspect of your enterprise:

• People: empower various users, collaborate across teams, use best practices and CoEs
• Processes: support the end-to-end ML process, establish ML ops, institute auditability, transparency, and governance
• Technology: Automate and ruse, use a data science platform to orchestrate open source complexity, and consider performance, scalability, and the IoT