In our last post about machine learning, we went over what MLOps is and touched on the benefits. In this post, we go deeper into the benefits of automated machine learning (AutoML).
1. Faster Time to Value – and Innovation
This is often the top benefit when making a case for purchasing an automated solution because it is tied to return on investment. With AutoML, projects can be released in hours or even minutes and iterated upon just as quickly as the team learns and expands projects.
2. Accelerated Scalability
Thousands of models can be deployed, overseen, and expanded upon for continuous delivery and deployment. Users quickly create models across different products and new business use cases with a reduced risk of human-based errors.
3. Operational Excellence
AutoML takes some of the risks out of data sciences projects. Not only are the models maintained for you, but if there are personnel changes, the knowledge transfer is likely to be more seamless and successful.
4. Democratized AI:
Automating the ML process empowers analysts and analytically inclined business owners to run their own AI projects. This allows data scientists to focus on more complex, cross-functional data science projects.
Squark’s tool provides end-to-end automation of the entire data science, AutoML process. Data ingestion, preparation, feature engineering, training, modeling, and displaying results are all handled by Squark in a matter of clicks. Ongoing maintenance is also taken care of by Squark. Models can be updated manually or set on a schedule, so you know you’re always working with the most up-to-date data.
Automate your machine learning so that you can do more. More growing, more learning, more focusing on the aspects of your job that most interest you to drive the business forward.
Schedule a time to speak to one of our reps and learn more about Squark can help you meet your goals.
Judah Phillips