AWS Machine Learning Blog

Category: Intermediate (200)

Optimize hyperparameters with Amazon SageMaker Automatic Model Tuning

Machine learning (ML) models are taking the world by storm. Their performance relies on using the right training data and choosing the right model and algorithm. But it doesn’t end here. Typically, algorithms defer some design decisions to the ML practitioner to adopt for their specific data and task. These deferred design decisions manifest themselves […]

Implementing Amazon Forecast in the retail industry: A journey from POC to production

Amazon Forecast is a fully managed service that uses statistical and machine learning (ML) algorithms to deliver highly accurate time-series forecasts. Recently, based on Amazon Forecast, we helped one of our retail customers achieve accurate demand forecasting, within 8 weeks. The solution improved the manual forecast by an average of 10% in regards to the […]

Real-time analysis of customer sentiment using AWS

Companies that sell products or services online need to constantly monitor customer reviews left on their website after purchasing a product. The company’s marketing and customer service departments analyze these reviews to understand customer sentiment. For example, marketing could use this data to create campaigns targeting different customer segments. Customer service departments could use this […]

Easy and accurate forecasting with AutoGluon-TimeSeries

AutoGluon-TimeSeries is the latest addition to AutoGluon, which helps you easily build powerful time series forecasting models with as little as three lines of code. Time series forecasting is a common task in a wide array of industries as well as scientific domains. Having access to reliable forecasts for supply, demand, or capacity is crucial […]

Build high performing image classification models using Amazon SageMaker JumpStart

Image classification is a computer vision-based machine learning (ML) technique that allows you to classify images. Some well-known examples of image classification include classifying handwritten digits, medical image classification, and facial recognition. Image classification is a useful technique with several business applications, but building a good image classification model isn’t trivial. Several considerations can play […]

Malware detection and classification with Amazon Rekognition

According to an article by Cybersecurity Ventures, the damage caused by Ransomware (a type of malware that can block users from accessing their data unless they pay a ransom) increased by 57 times in 2021 as compared to 2015. Furthermore, it’s predicted to cost its victims $265 billion (USD) annually by 2031. At the time […]

How to schedule jobs and parameterize your datasets in Amazon SageMaker Data Wrangler

Data is transforming every field and every business. However, with data growing faster than most companies can keep track of, collecting data and getting value out of that data is a challenging thing to do. A modern data strategy can help you create better business outcomes with data. AWS provides the most complete set of […]

Refit trained parameters on large datasets using Amazon SageMaker Data Wrangler

Amazon SageMaker Data Wrangler helps you understand, aggregate, transform, and prepare data for machine learning (ML) from a single visual interface. It contains over 300 built-in data transformations so you can quickly normalize, transform, and combine features without having to write any code. Data science practitioners generate, observe, and process data to solve business problems […]

Amazon SageMaker Studio Lab continues to democratize ML with more scale and functionality

To make machine learning (ML) more accessible, Amazon launched Amazon SageMaker Studio Lab at AWS re:Invent 2021. Today, tens of thousands of customers use it every day to learn and experiment with ML for free. We made it simple to get started with just an email address, without the need for installs, setups, credit cards, […]

Identifying and avoiding common data issues while building no code ML models with Amazon SageMaker Canvas

Business analysts work with data and like to analyze, explore, and understand data to achieve effective business outcomes. To address business problems, they often rely on machine learning (ML) practitioners such as data scientists to assist with techniques such as utilizing ML to build models using existing data and generate predictions. However, it isn’t always […]