Category: HAQM Machine Learning

Dataiku orchestrates the entire machine learning lifecycle and makes it accessible to data scientists and analysts alike. With deep integration with AWS AI tools, Dataiku enables users to augment their analytics workflow with pretrained NLP and computer vision models. Learn how you can use HAQM Comprehend and HAQM Rekognition plugins on Dataiku Data Science Studio (DSS) to build a simple workflow of NLP and computer vision use cases, respectively.

Building effective machine learning models requires storing and managing historical data, but conventional databases can quickly become a nightmare to regulate. Queries start taking too long, for example, slowing down business decisions. Learn how to use HAQM Redshift ML and Query Editor V2 to create, train, and apply ML models to predict diabetes cases for a sample diabetes dataset. You can follow a similar approach to address other use cases such as customer churn prediction and fraud detection.

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.

Leveraging data to make better decisions is critical for driving optimal business outcomes. Palantir empowers organizations to rapidly extract maximum value from one of their most valuable assets—their data. Palantir Foundry solves for the real-world application of AI, and not how it works in the lab. Effective AI is impossible without a trustworthy data foundation, a representation of an institution’s decisions, and the infrastructure to learn from every decision made.

With exponential increases in the amount of visual data such as images and videos being generated, image analytics is fast becoming a major business driver for many organizations. The Deloitte Image Recognition Framework is a cloud-based image recognition platform leveraging machine learning to automatically distinguish between two images. It helps customers deploy image recognition and analytics solutions and customize it per their business requirements.

Asset integrity management is a key activity for energy companies, and with recent advances in the field of machine learning, specifically computer vision, there are digital technologies that can enhance customers’ existing workflows and help plan preventative work. Learn how Wipro’s visual inspection and integrity management solution, InspectAI, can help customers deploy a cloud-based solution and transform their inspection process on AWS.

There is broad acceptance that AI and ML will help improve health outcomes for patients, and make healthcare more affordable. Data Science as a Service (DSaaS) from Change Healthcare is a secure, managed, healthcare data science platform that customers can leverage the embedded datasets and load their own datasets to be linked to deliver transformative and compliant insights. Learn how Change Healthcare built DSaaS to address the needs of practitioners developing AI/ML algorithms.

Despite the investments and commitment from leadership, many organizations are yet to realize the full potential of artificial intelligence (AI) and machine learning (ML). How can data science and analytics teams tame complexity and live up to the expectations placed on them? MLOps provides some answers. Hear from AWS Premier Consulting Partner Reply how you can “glue” the various components of MLOps together to build an MLOps solution using AWS managed services.

HAQM Connect is an easy-to-use cloud contact center platform that helps enterprises provide superior customer service at a lower cost. TCS has built an adapter that can pick up the customer queries from social messenger channels and bring them into the web chat channel of HAQM Connect. This post describes the high-level architecture of the TCS solution, potential benefits, and ways to extend the solution to leverage other AWS services.

Organizations that have foresight into their business have a competitive advantage. Advanced analytics that enable foresight have historically required scarce resources to develop predictive models using techniques like machine learning. Traditionally, this is a difficult endeavor, but recent progress in ML automation has made democratization of ML a possibility. Learn about the value of augmenting analytics with ML through the HAQM SageMaker for Tableau Quick Start.