Artificial Intelligence
Category: Amazon Machine Learning
Perform interactive data engineering and data science workflows from Amazon SageMaker Studio notebooks
Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). With a single click, data scientists and developers can quickly spin up Studio notebooks to explore and prepare datasets to build, train, and deploy ML models in a single pane of glass. We’re excited to announce a new set of […]
Launch Amazon SageMaker Studio from external applications using presigned URLs
Amazon SageMaker Studio provides a single, web-based visual interface where you can perform all ML development steps, improving data science team productivity by up to 10 times. Studio gives you complete access, control, and visibility into each step required to build, train, and deploy models. You can quickly upload data, create new notebooks, train and […]
AWS is redefining how companies process documents in a digital world
Think about the last time you opened a bank account, applied for insurance, or refinanced your home. It was probably done on paper. The number of documents in a mortgage packet alone is over 100 pages long. What do you do with all that paper? For many companies across a variety of industries, including financial […]
Introducing PII identification and redaction in streaming transcriptions using Amazon Transcribe
Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech to text capabilities to their applications. Since launching in 2017, Amazon Transcribe has added numerous features to enhance its capabilities around converting speech to text. Some of these features include automatic language detection, custom language models, vocabulary […]
How to redact personally identifiable information from audio files with Amazon Transcribe
Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy to add speech-to-text capabilities to your applications. Speech or audio data is virtually impossible for computers to search and analyze. Therefore, recorded speech needs to be converted to text before it can be used in applications. Automatic content redaction is a feature […]
Manage your Amazon Fraud Detector resources in an automated and secure manner using AWS CloudFormation
Amazon Fraud Detector is a fully managed service that makes it easy to identify potentially fraudulent online activities, such as the creation of fake accounts or online payment fraud. Unlike general-purpose machine learning (ML) packages, Amazon Fraud Detector is designed specifically to detect fraud. Amazon Fraud Detector combines your data, the latest in ML science, […]
The development of Bundesliga Match Fact Passing Profile, a deep dive into passing in football
This post was authored by Simon Rolfes. Simon played 288 Bundesliga games as a central midfielder, scored 41 goals, and won 26 caps for Germany. Currently, he serves as Sporting Director at Bayer 04 Leverkusen, where he oversees and develops the pro player roster, the scouting department, and the club’s youth development. Simon also writes […]
Boost transcription accuracy of class lectures with custom language models for Amazon Transcribe
Many universities like transcribing their recorded class lectures and later creating captions out of these transcriptions. Amazon Transcribe is a fully-managed automatic speech recognition service (ASR) that makes it easy to add speech-to-text capabilities to voice-enabled applications. Transcribe assists in increasing accessibility and improving content engagement and learning outcomes by connecting with both auditory and […]
Fully customizable action space now available on the AWS DeepRacer console
AWS DeepRacer is the fastest way to get rolling with machine learning (ML) through a global racing league, cloud-based 3D racing simulator, and fully autonomous 1/18th scale race car driven by reinforcement learning. Starting today, the model action space is fully customizable yet simplified with new dynamic graphics so developers have greater control and can […]
Define and run Machine Learning pipelines on Step Functions using Python, Workflow Studio, or States Language
May 2024: This post was reviewed and updated for accuracy. You can use various tools to define and run machine learning (ML) pipelines or DAGs (Directed Acyclic Graphs). Some popular options include AWS Step Functions, Apache Airflow, KubeFlow Pipelines (KFP), TensorFlow Extended (TFX), Argo, Luigi, and Amazon SageMaker Pipelines. All these tools help you compose […]





