One of the hottest announcements at this years AWS re:Invent
The ability to build systems that can predict business outcomes has become very important within the last few years. This ability lets you solve problems and move faster by automating slow processes and embedding intelligence in almost all IT systems.
But how do you make sure that all team and individual decision makers in the organization are empowered to create these machine learning (ML) systems at scale, without depending on other data science and data engineering teams?
As a business user or data analyst, you’d like to build and use prediction systems based on the data that you analyze and process every day, without having to learn about hundreds of algorithms, training parameters, evaluation metrics and deployment best practices.
At this year’s re:Invent in Las Vegas, AWS announced the general availability of Amazon SageMaker Canvas, a new visual, no code capability that allows business analysts to build ML models and generate accurate predictions without writing code or requiring ML expertise. Its intuitive user interface lets you browse and access disparate data sources in the cloud or on-premises, combine datasets with the click of a button, train accurate models and then generate new predictions once new data is available.
SageMaker Canvas leverages the same technology as Amazon SageMaker to automatically clean and combine your data, create hundreds of models under the hood, select the best performing one and generate new individual or batch predictions. It supports multiple problem types such as binary classification, multi-class classification, numerical regression and time series forecasting. These problem types let you address business-critical use cases, such as fraud detection, churn reduction and inventory optimization, without writing a single line of code!
Preparing to create and inspect models and data in the SageMaker Canvas Dashboard.
Generally available from today!
SageMaker Canvas is generally available from today in US East (Ohio), US East (N. Virginia), US West (Oregon), Europe (Frankfurt) and Europe (Ireland).
You can start using it with local datasets, as well as data already stored on Amazon S3, Amazon Redshift or Snowflake. With just a few clicks, you can prepare and join your datasets, analyse estimated accuracy, verify which columns are impactful, train the best performing model and generate new individual or batch predictions.
Intuitive UI to look at predictive outcomes of datasets.
Eyes on the prize
As an Advanced AWS Partner with a keen use of predictive models and ML fed analytics, the announcement of SageMaker Canvas has got us all very excited.
The ability to craft predictive models based on datasets without needing advanced coding and data science experience does nothing but open the doors to faster predictive ML based models for client projects. The addition of SageMaker Canvas to SageMaker enables more of our team to get hands on experience creating models and training data without the need for years of experience in coding data manually.
If you’d like to see SageMaker Canvas in action, please visit the official blog post that announced the new service.
Alternatively, you can reach out to us below and begin your data journey with this exciting new tool. Firemind is a data focused partner that can quickly organise, train and get your data working for you!