Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. No machine learning experience required. There is a treasure trove of potential sitting in your unstructured data. Customer emails, support tickets, product reviews, social media, even advertising copy represents insights into customer sentiment that can be put to work for your business. The question is how to get at it? As it turns out, Machine learning is particularly good at accurately identifying specific items of interest inside vast swathes of text (such as finding company names in analyst reports), and can learn the sentiment hidden inside language (identifying negative reviews, or positive customer interactions with customer service agents), at almost limitless scale. Amazon Comprehend uses machine learning to help you uncover the insights and relationships in your unstructured data. The service identifies the language of the text; extracts key phrases, places, people, brands, or events; understands how positive or negative the text is; analyzes text using tokenization and parts of speech; and automatically organizes a collection of text files by topic. You can also use AutoML capabilities in Amazon Comprehend to build a custom set of entities or text classification models that are tailored uniquely to your organization’s needs. For extracting complex medical information from unstructured text, you can use Amazon Comprehend Medical. The service can identify medical information, such as medical conditions, medications, dosages, strengths, and frequencies from a variety of sources like doctor’s notes, clinical trial reports, and patient health records. Amazon Comprehend Medical also identifies the relationship among the extracted medication and test, treatment and procedure information for easier analysis. For example, the service identifies a particular dosage, strength, and frequency related to a specific medication from unstructured clinical notes.
Amazon Fraud Detector
Reduce online payment fraud by flagging suspicious online payment transactions before processing payments and fulfilling orders. With Amazon Fraud Detector, you can setup your checkout flow to evaluate new orders and flag suspicious ones for review prior to processing payments. Spot potential fraudsters among customers without transaction histories. With Amazon Fraud Detector, you can send as little as two pieces of data from a guest checkout order (e.g., email, IP address) to assess its potential fraud risk, so you can decide whether to accept it, review it, or collect more customer details. Online service and loyalty program abuse Identify accounts that are more likely to abuse online services such as loyalty or ‘Try Before You Buy’ programs that ship goods for customers to try before sending payment. With Amazon Fraud Detector, online businesses can help assess the risk of customers abusing programs, for example by stealing merchandise or engaging in returns abuse, so businesses can limit their risks by applying appropriate limits on the value of goods or services provided.
Amazon Polly is a service that turns text into lifelike speech, allowing you to create applications that talk, and build entirely new categories of speech-enabled products. Polly’s Text-to-Speech (TTS) service uses advanced deep learning technologies to synthesize natural sounding human speech. With dozens of lifelike voices across a broad set of languages, you can build speech-enabled applications that work in many different countries. In addition to Standard TTS voices, Amazon Polly offers Neural Text-to-Speech (NTTS) voices that deliver advanced improvements in speech quality through a new machine learning approach. Polly’s Neural TTS technology also supports two speaking styles that allow you to better match the delivery style of the speaker to the application: a Newscaster reading style that is tailored to news narration use cases, and a Conversational speaking style that is ideal for two-way communication like telephony applications. Finally, Amazon Polly Brand Voice can create a custom voice for your organization. This is a custom engagement where you will work with the Amazon Polly team to build an NTTS voice for the exclusive use of your organization.
Amazon Rekognition makes it easy to add image and video analysis to your applications using proven, highly scalable, deep learning technology that requires no machine learning expertise to use. With Amazon Rekognition, you can identify objects, people, text, scenes, and activities in images and videos, as well as detect any inappropriate content. Amazon Rekognition also provides highly accurate facial analysis and facial search capabilities that you can use to detect, analyze, and compare faces for a wide variety of user verification, people counting, and public safety use cases. With Amazon Rekognition Custom Labels, you can identify the objects and scenes in images that are specific to your business needs. For example, you can build a model to classify specific machine parts on your assembly line or to detect unhealthy plants. Amazon Rekognition Custom Labels takes care of the heavy lifting of model development for you, so no machine learning experience is required. You simply need to supply images of objects or scenes you want to identify, and the service handles the rest.
<p>Easily extract text and data from your documents!</p>
<p>Amazon Textract is a service that automatically detects and extracts text and data from scanned documents. It goes beyond simple optical
character recognition (OCR) to also identify the contents of fields in forms and information stored in tables.</p>
<p>Scan documents such as balance sheets, tax forms, insurance clams forms, medical notes and credit applications.</p><br/>
Amazon Transcribe makes it easy for developers to add speech to text capabilities to their applications. 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. Historically, customers had to work with transcription providers that required them to sign expensive contracts and were hard to integrate into their technology stacks to accomplish this task. Many of these providers use outdated technology that does not adapt well to different scenarios, like low-fidelity phone audio common in contact centers, which results in poor accuracy. Transcribe uses a deep learning process called automatic speech recognition (ASR) to convert speech to text quickly and accurately. Transcribe can be used to transcribe customer service calls, automate subtitling, and generate metadata for media assets to create a fully searchable archive. You can use Transcribe Medical to add medical speech to text capabilities to clinical documentation applications.
Amazon Translate is a neural machine translation service that delivers fast, high-quality, and affordable language translation. Neural machine translation is a form of language translation automation that uses deep learning models to deliver more accurate and more natural sounding translation than traditional statistical and rule-based translation algorithms. With Amazon Translate, you can localize content such as websites and applications for your diverse users, easily translate large volumes of text for analysis, and efficiently enable cross-lingual communication between users.