This is a short refresher of the 7 AWS machine learning services announced at Re:invent 2018 which will cover:
- Amazon SageMaker Ground Truth
- Amazon Forecast
- Amazon Comprehend Medical
- Amazon Textract
- Amazon Personalize
- Amazon SageMaker RL
- AWS DeepRacer
- It aims to provide an awareness of what each of the ML services is used for and the benefit that they can bring to you within your organization
- This course would be beneficial to anyone who is responsible for implementing, managing, and securing machine learning services within AWS
- You should have a basic understanding of Machine learning concepts and principles to help you understand how each of these services fit into the AWS landscape
Related Training Content
Introduction to Machine Learning on AWS
Applying Machine Learning and AI Services on AWS
OCR or Optical Character Recognition has been around for a long time. You'll see OCR heavily used as a method to extract data contained within images or PDFs of questionnaires and/or surveys. This approach is often implemented to avoid manual data entry, saving on both time and labor. Although a proven technology, traditional OCR does have limitations.
Amazon Textract on the other hand, is OCR on steroids. Built and provided by Amazon, Amazon Textract, under the hood, leverages machine learning to provide a level of service that surpasses many existing OCR solutions. One area where Amazon Textract excels is in scanning documents that contain tabulated information, and tables of figures, et cetera. Amazon Textract will not only recognize the characters within a table, but will maintain and format the table in the output. It can do so, because underneath, it's using machine learning technology.
As already mentioned, Amazon Textract uses a machine learning model which has been trained on millions of documents, enabling it to detect and read special formatting features contained within any document. Complex layouts and formats used with many form-based documents can easily be detected, and therefore rendered back into the OCR-ed format. For example, financial, medical and/or tax-based forms tend to leverage many formats and structures to layout the questionnaire fields. Amazon Textract can intelligently detect these structures, extract and record them, and then encode them as key value pairs. Amazon Textract performs OCR on documents in either PNG, JPEG, or PDF formats. Documents can be submitted both synchronously or asynchronously, with APIs provided to support both methods. Uploaded documents into the Amazon Textract service can be deleted, and regardless, ownership of any uploaded document remains with the AWS account holder, and as such cannot be used anytime afterwards without their express consent.
Amazon Textract has been seamlessly integrated into other AWS services, such as Amazon S3, AMS Lambda, AWS Batch and Amazon Elasticsearch Service. This allows you to quickly rollout solutions that encompass search and find features across your corpus of scanned documents. When working with Amazon Textract you can use the Amazon Textract console, or either the AWS CLI, or Java or Python SDKs. Over time, additional SDKs will be upgraded to provide Textract support.
So, let's quickly summarize the key features that distinguish Amazon Textract as an OCR service. Machine Learning technology is used behind the scenes. Key-Value Pair and Table Extraction possible, with results encoded in JSON format. Bounding Box coordinates are provided, which can be referenced to determine exactly where the data was detected and extracted from. Confidence Thresholds are provided as a measure of confidence in terms of what was recognized and translated. If you're in need of an OCR solution that raises the bar and turns up performance, feature sets, and is both low-cost and pay-as-you-go, then Amazon Textract could be the right service.
Stuart has been working within the IT industry for two decades covering a huge range of topic areas and technologies, from data center and network infrastructure design, to cloud architecture and implementation.
To date, Stuart has created 150+ courses relating to Cloud reaching over 180,000 students, mostly within the AWS category and with a heavy focus on security and compliance.
Stuart is a member of the AWS Community Builders Program for his contributions towards AWS.
He is AWS certified and accredited in addition to being a published author covering topics across the AWS landscape.
In January 2016 Stuart was awarded ‘Expert of the Year Award 2015’ from Experts Exchange for his knowledge share within cloud services to the community.
Stuart enjoys writing about cloud technologies and you will find many of his articles within our blog pages.