Most organizations would like to start using machine learning to inform the decisions they make every day. But, if you don’t already have a full data science team, where do you start?

In this video, we will discuss the entry options for creating machine learning models and achieving machine learning outputs. To do this we will show you how easily you can get started with running AutoML experiments and creating your own ML models using drag and drop tools that require no coding experience. Finally, we cover how you can advance to the next step of creating and customizing an ML model using code (Python/Pyspark).

The video covers:

• Basics of machine learning
• Demos and explanation of no code machine learning development options (Vertex AI’s AutoML, Azure ML Studio)
• Demo and explanation of coding a machine learning model in Databricks

Is it for you:

• Do you want to understand machine learning?
• Do you want to see the options to try machine learning for yourself?

If you liked this video, make sure to check out the rest of ‘The Stages of your Analytics Journey’ video series. In this series we talk through each stage of the journey that an organization can undergo to effectively apply machine learning (ML) to their data to find insights and inform decisions. From the beginning steps of creating an ML model, all the way through to having a successful productionized solution that the business understands and uses repeatedly, and every stage in between. Parts 2, 3, and 4 are linked below.