Steps of The Machine Learning Pipeline
There are a number of steps that go into building a machine learning pipeline, and each step can be a laborious and time-consuming process with highly unpredictable costs when attempting it yourself . Cortex takes the guesswork out of the ML pipelines by automating it from start to finish.
Say Goodbye to Data Wrangling
Some businesses might already have a team to tackle data wrangling. However, it typically accounts for 90-95% of the effort in building a machine learning pipeline, and progress is often slowed by the unforeseen challenges it presents. With these steps automated for you in Cortex, your team is free to focus on strategy and apply the results.
Repeatable, Re-trainable ML Pipelines - in Seconds
Retraining models with new data takes a lot of additional effort when the data needs to be pulled together, cleaned and engineered all over again. With Cortex, retraining models is just one click away. As your data streams into the platform, pipelines can be scheduled to run on a recurring basis so you always have the highest quality results at the tips of your fingers.
Getting Started is Easy
Schedule a demo, set up a free trial, and
start saving time and money deploying ML.