*Machine Learning*

Question 1

Amazon Augmented AI

Answer 1

Amazon Augmented AI (Amazon A2I) is a machine learning service which makes it easy to build the workflows required for human review.

Amazon A2I brings human review to all developers, removing the undifferentiated heavy lifting associated with building human review systems or managing large numbers of human reviewers whether it runs on AWS or not.

Question 2

Amazon CodeGuru

Answer 2

Amazon CodeGuru is a developer tool that provides intelligent recommendations to improve code quality and identify an application’s most expensive lines of code.

Integrate CodeGuru into your existing
software development workflow to automate code reviews during application development and continuously monitor application’s performance in production and provide recommendations and visual
clues on how to improve code quality, application performance, and reduce overall cost.

Question 3

Amazon Comprehend

Answer 3

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.

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.

Question 4

Amazon DevOps Guru

Answer 4

Amazon DevOps Guru is a Machine Learning (ML) powered service that makes it easy to improve an application’s operational performance and availability.

DevOps Guru detects behaviors that deviate
from normal operating patterns so you can identify operational issues long before they impact your customers.

DevOps Guru uses machine learning models informed by years of Amazon.com and AWS operational excellence to identify anomalous application behavior (e.g. increased latency, error rates, resource constraints, etc.) and surface critical issues that could cause potential outages or service disruptions.

When DevOps Guru identifies a critical issue, it automatically sends an alert and provides a summary of related anomalies, the likely root cause, and context about when and where the issue occurred, and provides recommendations on how to remediate the issue.

Question 5

Amazon Elastic Inference

Answer 5

Amazon Elastic Inference allows you to attach low-cost GPU-powered acceleration to Amazon EC2 and Amazon SageMaker instances to reduce the cost of running deep learning inference by up to 75%.
Amazon Elastic Inference supports TensorFlow, Apache MXNet, PyTorch, and ONNX models.

Choose the instance type that is best suited to the overall CPU and memory needs of your application, and then separately configure the amount of inference acceleration that you need to use resources efficiently and to reduce the cost of running inference

Question 6

Amazon Forecast

Answer 6

Amazon Forecast is a fully managed service that uses machine learning to deliver highly accurate forecasts.

Amazon Forecast uses machine learning to combine time series data with additional variables to build forecasts. Amazon Forecast
will produce a forecasting model capable of making predictions that are up to 50% more accurate than looking at time series data alone.

You pay only for what you use, and there are no minimum fees and no upfront commitments.

Question 7

Amazon Fraud Detector

Answer 7

Amazon Fraud Detector is a fully managed service that uses machine learning (ML) and more than 20 years of fraud detection expertise from Amazon, to identify potentially fraudulent activity so customers can catch more online fraud faster.

Amazon Fraud Detector automates the time consuming and expensive steps to build, train, and deploy an ML model for fraud detection.

Pay only for what you use, avoiding large upfront expenses.

Question 8

Amazon HealthLake

Answer 8

Amazon HealthLake is a HIPAA-eligible service that healthcare providers, health insurance companies, and pharmaceutical companies can use to store, transform, query, and analyze large-scale health data.

Healthcare providers can use HealthLake to store, transform, query, and analyze data in the AWS Cloud. Using the HealthLake integrated medical natural language processing (NLP) capabilities, you can analyze unstructured clinical text from diverse sources.* HealthLake transforms unstructured data using natural language processing models, and *provides powerful query and search capabilities. You can use HealthLake to organize, index, and structure patient information in a secure, compliant, and auditable manner.

Question 9

Amazon Kendra

Answer 9

Amazon Kendra is an intelligent search service powered by machine learning.

Amazon Kendra is a fully managed service, so there are no servers to provision, and no machine learning models to build, train, or deploy.

Question 10

Amazon Lex

Answer 10

Amazon Lex is a service for building conversational interfaces into any application using voice and text.

Lex provides the advanced deep learning functionalities of automatic speech recognition (ASR) for converting speech to text, and natural language understanding (NLU) to recognize the intent of the text, to enable you to build applications with highly engaging user experiences and lifelike conversational interactions.

Question 11

Amazon Lookout for Equipment

Answer 11

Amazon Lookout for Equipment analyzes the data from the sensors on your equipment (e.g. pressure in a generator, flow rate of a compressor, revolutions per minute of fans), to automatically train a machine learning model based on just your data, for your equipment – with no ML expertise required.

Lookout for Equipment uses your unique ML model to analyze incoming sensor data in real-time and accurately identify early warning signs that could lead to machine failures.

Question 12

Amazon Lookout for Metrics

Answer 12

Amazon Lookout for Metrics uses machine learning (ML) to automatically detect and diagnose anomalies (i.e. outliers from the norm) in business and operational data, such as a sudden dip in sales revenue
or customer acquisition rates.

Amazon Lookout for Metrics a_utomatically inspects and prepares the data from sources to detect anomalies with greater speed and accuracy than traditional methods_ used for anomaly detection.

Question 13

Amazon Lookout for Vision

Answer 13

Amazon Lookout for Vision is a machine learning (ML) service that spots defects and anomalies in visual representations using computer vision (CV).

Amazon Lookout for Vision allows customers to eliminate the need for costly and inconsistent manual inspection, while improving quality control, defect and damage assessment, and compliance.

Question 14

Amazon Monitron

Answer 14

Amazon Monitron is an end-to-end system that uses machine learning (ML) to detect abnormal behavior in industrial machinery, enabling you to implement predictive maintenance and reduce unplanned
downtime.

Amazon Monitron includes sensors to capture vibration and temperature data from equipment, a gateway device to securely transfer data to AWS, the Amazon Monitron service that a_nalyzes the data for_
abnormal machine patterns using machine learning, and a companion mobile app to set up the devices and receive reports on operating behavior and alerts to potential failures in your machinery.

Question 15

Amazon Personalize

Answer 15

Amazon Personalize is a machine learning service that makes it easy for developers to create individualized recommendations for customers using their applications.

With Amazon Personalize, you provide an activity stream from your application – page views, signups, purchases, and so forth – as well as an inventory of the items you want to recommend, such as articles, products, videos, or music.

You can also choose to provide Amazon Personalize with additional demographic information from your users such as age, or geographic location. Amazon Personalize will process and examine the data, identify what is meaningful, select the right algorithms, and train and optimize a personalization model that is customized for your data. All data analyzed by Amazon Personalize is kept private and secure, and only used for your customized recommendations.

You pay only for what you use, and there are no minimum fees and no upfront commitments.

Question 16

Amazon Polly

Answer 16

Amazon Polly is a service that turns text into lifelike speech.

Polly lets you create applications that talk, enabling you to build entirely new categories of speech-enabled products.

Polly is an Amazon artificial intelligence (AI) service that uses advanced deep learning technologies to synthesize speech that sounds like a human voice.

Question 17

Amazon Rekognition

Answer 17

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. 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.

Question 18

Amazon SageMaker

Answer 18

Amazon SageMaker is a fully-managed service that enables developers and data scientists to quickly and easily build, train, and deploy machine learning models at any scale.

SageMaker includes modules that can be used together or independently to build, train, and deploy your machine learning models

Question 19

Amazon SageMaker Ground Truth

Answer 19

Amazon SageMaker Ground Truth helps you build highly accurate training datasets for machine learning quickly.

SageMaker Ground Truth offers easy access to public and private human labelers and provides them with built-in workflows and interfaces for common labeling tasks.

Lower your labeling costs by up to 70% using automatic labeling, which works by training
Ground Truth from data labeled by humans so that the service learns to label data independently. Amazon SageMaker Ground Truth significantly reduces the time and effort required to create datasets for training to reduce costs. SageMaker Ground Truth can label more and more data automatically and substantially speed up the creation of training datasets.

Question 20

Amazon Textract

Answer 20

Amazon Textract is a service that automatically extracts text and data from scanned documents.

Amazon Textract goes beyond simple optical character recognition (OCR) to also identify the contents of fields in forms and information stored in tables.

Amazon Textract uses machine learning to instantly “read” virtually any type of document to accurately extract text and data without the need for any manual effort or custom code.

Create smart search indexes, build automated approval workflows, and better maintain compliance with document archival rules by flagging data that may require redaction.

Question 21

Amazon Transcribe

Answer 21

Amazon Transcribe is an automatic speech recognition (ASR) service that makes it easy for developers to add speech-to-text capability to their applications.

Using the Amazon Transcribe API, you can analyze audio files stored in Amazon S3 and have the service return a text file of the transcribed speech. You can also send a live audio stream to Amazon Transcribe and receive a stream of transcripts in real time.

Amazon Transcribe can be used for lots of common applications, including the transcription of customer service calls and generating subtitles on audio and video content. The service can transcribe audio files stored in common formats, like WAV and MP3, with time stamps for every word so that you can easily locate the audio in the original source by searching for the text.

Question 22

Amazon Translate

Answer 22

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.*

Amazon Translate allows you to localize content - such as websites and applications - for international users, and to easily translate large volumes of text efficiently.

Question 23

Apache MXNet on AWS

Answer 23

Apache MXNet on AWS is a fast and scalable training and inference framework with an easy-to-use, concise API for machine learning.

MXNet includes the Gluon interface that allows developers of all skill levels to get started with deep learning on the cloud, on edge devices, and on mobile apps. In just a few lines of Gluon code, you can build linear regression, convolutional networks and recurrent LSTMs for object detection, speech
recognition, recommendation, and personalization.

You can get started with MxNet on AWS with a fully-managed experience using SageMaker, a platform to build, train, and deploy machine learning models at scale. Or, you can use the AWS Deep Learning AMIs to build custom environments and workflows with MxNet as well as other frameworks including TensorFlow, PyTorch, Chainer, Keras, Caffe, Caffe2, and Microsoft Cognitive Toolkit.

Question 24

AWS Deep Learning AMIs

Answer 24

The AWS Deep Learning AMIs provide machine learning practitioners and researchers with the infrastructure and tools to accelerate deep learning in the cloud, at any scale.

Quickly launch Amazon EC2 instances pre-installed with popular deep learning frameworks such as Apache MXNet and
Gluon, TensorFlow, Microsoft Cognitive Toolkit, Caffe, Caffe2, Theano, Torch, PyTorch, Chainer, and Keras to train sophisticated, custom AI models, experiment with new algorithms, or to learn new skills and techniques.

Question 25

AWS DeepComposer

Answer 25

AWS DeepComposer is the world’s first musical keyboard powered by machine learning to enable developers of all skill levels to learn Generative AI while creating original music outputs.

DeepComposer consists of a USB keyboard that connects to the developer’s computer, and the DeepComposer service, accessed through the AWS Management Console. DeepComposer includes tutorials, sample code, and training data that can be used to start building generative models.

Question 26

AWS DeepLens

Answer 26

AWS DeepLens helps put deep learning in the hands of developers, literally, with a fully programmable video camera, tutorials, code, and pre-trained models designed to expand deep learning skills.

Question 27

AWS DeepRacer

Answer 27

AWS DeepRacer is a 1/18th scale race car which gives you an interesting and fun way to get started with reinforcement learning (RL).

RL is an advanced machine learning (ML) technique which takes a very
different approach to training models than other machine learning methods. Its super power is that it learns very complex behaviors without requiring any labeled training data, and can make short term
decisions while optimizing for a longer term goal. With AWS DeepRacer, you now have a way to get hands-on with RL, experiment, and learn through autonomous driving. You can get started with the virtual car and tracks in the cloud-based 3D racing simulator, and for a real-world experience, you can deploy your trained models onto AWS DeepRacer and race your friends, or take part in the global AWS DeepRacer League. Developers, the race is on.

Question 28

AWS Inferentia

Answer 28

AWS Inferentia is a machine learning inference chip designed to deliver high performance at low cost.

AWS Inferentia will support the TensorFlow, Apache MXNet, and PyTorch deep learning frameworks, as well as models that use the ONNX format. Making predictions using a trained machine learning model–a process called inference–can drive as much
as 90% of the compute costs of the application. Using Amazon Elastic Inference, developers can r_educe inference costs by up to 75%_ by attaching GPU-powered inference acceleration to Amazon EC2 and SageMaker instances.

AWS Inferentia provides high throughput, low latency inference performance at an extremely low cost. Each chip provides hundreds of TOPS (tera operations per second) of inference throughput to allow complex models to make fast predictions. For even more performance, multiple AWS Inferentia chips can be used together to drive thousands of TOPS of throughput. AWS Inferentia will be available for use with SageMaker, Amazon EC2, and Amazon Elastic Inference.

Question 29

TensorFlow on AWS

Answer 29

TensorFlow enables developers to quickly and easily get started with deep learning in the cloud. The framework has broad support in the industry and has become a popular choice for deep learning research and application development, particularly in areas such as computer vision, natural language
understanding and speech translation.
You can get started on AWS with a fully-managed TensorFlow experience with SageMaker, a platform to build, train, and deploy machine learning models at scale. Or, you can use the AWS Deep Learning AMIs
to build custom environments and workflows with TensorFlow and other popular frameworks including Apache MXNet, PyTorch, Caffe, Caffe2, Chainer, Gluon, Keras, and Microsoft Cognitive Toolkit.