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AWS Marketplace

Business Analytics

Detect anomalies, forecast demand, and personalize shopping experiences with business analytics.

Build AI and ML powered solutions faster

Gain valuable insights to improve your business

In a world driven by data, it is often challenging to find the right insights to build and expand your business. Machine learning-driven analytics can help you improve profitability by automating the detection of potentially fraudulent online activity, accurately predict demand and streamline supply-demand decisions, boost business productivity by delivering accurate and useful information faster, forecast business trends, and find hidden insights, such as anomalies or outliers, from your business data. 

Improving personalized ranking in recommender systems with Implicit BPR and Amazon SageMaker

Learn how to perform both batch and real-time inferences on a trained model.

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Solutions

The following solutions from AWS Marketplace sellers focus on Amazon Sagemaker for model delivery.

ElectrifAi

ElectrifAi company logo in black and yellow colors on a transparent background

ElectrifAi's Recommendation Engine builds customer ranking score models in different consumption categories to see the response in a certain campaign.

See how it works: Demo

 Try now 

Mphasis

Mphasis logo in color, horizontal orientation, 350x100 pixels

Financial Transactions Fraud Detection is a deep learning based algorithm capable of training on transactional data to detect fraudulent transactions.

See how it works: Demo

 Learn more 

Peak.ai

Logo for Peak AI Business Analytics, displayed in black and white text. Peak's 21 Day Forecast Challenge helps quantify, within 21 days, the financial opportunity that exists within your business via ML-driven forecasting. Learn more 

How to prepare your data pipeline for machine learning and AI

Get the practical guidance to help you prepare a data pipeline that can automate machine learning workflows.
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Benefits

Build ML applications faster

Plug and play pre-trained machine learning models from third-party sellers across various use cases without sharing the data outside your environment.

Reduce time for data prep

Use pre-trained models and solutions that can help identify high-quality data from your overall data set suitable for training the ML models.

Simple feature engineering

Leverage models and solutions to identify and extract additional features from your data that can be used to train your own downstream models.