Tag: AutoML

Learn how equipment operators can build a predictive maintenance solution using AutoML and no-code tools powered by AWS. This type of solution delivers significant gains to large-scale industrial systems and mission-critical applications where the costs associated with machine failure or unplanned downtime can be high. The design of this solution is based on the experience of Grid Dynamics with manufacturing clients.

Data-centric AI (DCAI) has been described as the discipline of systematically engineering the data used to build an AI system. It prescribes prioritizing improving data quality over tweaking algorithms to improve machine learning models. In this post, explore a DCAI solution built on Snowflake and Amazon SageMaker to serve as a factory for predictive analytics solutions. Learn about Snowflake’s integrations with SageMaker and get hands-on resources to help you put these capabilities into practice.

With multiple mediums of communication, like social media, television, and OTT, marketers are finding it difficult to understand the factors that impact ad conversions, and provide visibility into marketing campaigns. To address this challenge, Quantiphi worked with Advocado, an advertising focused data platform provider, to develop a solution for ad attribution of web traffic to respective offline and online sources on AWS.

Recognizing a user’s signature is an essential step in banking and legal transactions, and typically involves relying on human verification. Learn how Capgemini uses machine learning from AWS to build ML-models to verify signatures from different user channels including web and mobile apps. This ensures organizations can meet the required standards, recognize user identity, and assess if further verifications are needed.

Operationalizing machine learning models can be a challenge due to lack of established ML architecture and its integration with the existing landscape. DataRobot integrates with AWS and provides the flexibility for a model trained in DataRobot to be deployed on AWS services with centralized model governance, management, and monitoring. Learn how the DataRobot AutoML platform orchestrates the complete model development and training lifecycle.

Machine learning allows users to drive insights about their business, and the AutoML approach speeds up this process through the automation of ML pipeline steps. Learn how Domo created AutoML capabilities powered by Amazon SageMaker Autopilot, which is a fully managed AWS solution that automatically creates, trains, and tunes the best classification and regression ML models based on the data provided by a customer.

Time series forecasting is a common customer need. Amazon Forecast accelerates this and is based on the same technology used at Amazon.com. This new service massively reduces the effort required to automate data updating and model retraining, and it manages this while retaining the granularity of control that data scientists will appreciate and utilize. This post explores the use of this new service for energy consumption forecasting.