"人工智能 (AI) 與機器學習概覽 (Level 200) 講師： Jhen-wei Huang, Solutions Architect, AWS"

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Jhen-Wei Huang
Solutions Architect, Amazon Web Services
AWS人工智能與機器學習服務概覽

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Amazon.com,1995
At Amazon, we’ve been
making investments in
ML for the last 20
y ear s…

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Put Machine Learning in the hands of every developer
and data scientist
Our mission

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More machine learning is built on AWS than anywhere else

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Application
Services
Platform
Services
Frameworks
&
Infrastructure
API-driven services: Vision & Language Services, Conversational Chatbots
AWS ML Stack
Deploy machine learning models with high-performance machine learning
algorithms, broad framework support, and one-click training, tuning, and
inference.
Develop sophisticated models with any framework, create managed, auto-
scaling clusters of GPUs for large scale training, or run inference on trained
models.

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ML Application Services are designed for ease-of-use
Amazon data
science expertise
Amazon training
data
Amazon models
and learning
Accessibility
via API
Foundational components of Amazon AI/ML services
Scalable, trained, and continuously optimized services
that do not require extensive AI/ML expertise

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Enhancing the customer experience and uncovering insights
Polly
Turn text into lifelike speech
using deep learning
Lex
Conversational interfaces through
natural language understanding
Comprehend
Discover insights and
relationships in text
Transcribe
Add speech to text
capability to applications
Translate
More accurate and natural
sounding translation services
Rekognition
Facial and object recognition through
deep learning-based image analysis
Vision
Text
Language
Rekognition Video
Facial and object recognition through
deep learning-based video analysis

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Amazon Rekognition
Deep Learning-based image and video analysis service

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Object & Scene Detection

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Facial Analysis

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Crowd Detection – up to 100 faces

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Facial Search

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Explicit Nudity
Nudity
Graphic Male Nudity
Graphic Female Nudity
Sexual Activity
Partial Nudity
Suggestive
Female Swimwear or Underwear
Male Swimwear or Underwear
Revealing Clothes
Image Moderation

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Celebrity Recognition

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Text in Image

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Amazon Rekognition Video
Deep Learning-based video analysis service

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Video Analysis

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Build automatic analysis of body language to gauge
attention and engagement using Rekognition Video
https://aws.amazon.com/blogs/machine-learning/building-automatic-analysis-of-body-language-to-gauge-
attention-and-engagement-using-amazon-kinesis-video-streams-and-amazon-ai-services/

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Voice Is Now THE NEW STANDARD
Source: MindMeld
TIME
2 0 0 5 2 0 1 0 2 0 1 5 2 0 2 0
0 B
1 0 0 B
2 0 0 B
3 0 0 B
A Massive shift in voice has already begun.
• In 2014, voice search traffic was negligible.
Today it exceeds 10% of all search traffic.
• Virtual assistants exceed 50B voice
searches per month.
• By 2020, over 200 billion searches per
month will be done with voice.
K E Y W O R D
S E A R C H E S
V O I C E
S E A R C H E S
WORLD WIDE SEARCHES
PER MONTH

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VOICE IS EVERYWHERE
“Conversational platforms will drive the
next big paradigm shift in how humans
interact with the digital world.”
-Gartner Press Release, Gartner Identifies the Top 10
Strategic Technology Trends for 2018
October 4, 2017
Source: https://www.gartner.com/newsroom/id/3812063

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Alexa Made Voice the Mainstream UI at Home
“Alexa, call Jane”
“Alexa, order a pizza”
“Alexa, Start my TV”
“Alexa, lower the
temperature”
“Alexa, dim the lights”

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Alexa for Business

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Amazon Polly
Deep Learning-based text-to-speech service

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Amazon Polly
“Welcome to
AWS Seminar.
Today we are
going to
introduce AWS AI
& ML services”
Amazon Polly: Text In, Life-like Speech Out

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<speak xml:lang="en-US">
The price of this book is <prosody rate="60%">45€</prosody>
</speak>
A Focus On Voice Quality & Pronunciation
Support for Speech Synthesis Markup Language (SSML) Version 1.0
https://www.w3.org/TR/speech-synthesis

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AI Radio Announcer
• FM Wakayama staff focused on
gathering new information.
• Broadcast quality improved
considerably during the typhoon.
• Cached audio was free.

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Amazon Lex
Conversational Interfaces

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Intents
A particular goal that the
user wants to achieve
Utterances
Spoken or typed phrases
that invoke your intent
Slots
Data the user must provide to fulfill the
intent
Prompts
Questions that ask the user to input
data
Fulfillment
The business logic required to fulfill the
user’s intent
BookHotel

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Amazon Translate
Neural Machine Translation Service

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Automatic translation
Real-time
translation
Powered by Deep
Learning
12 Language pairs
(more to come)
Language detection

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Hotels.com
Machine Translation
« At Hotels.com, we are committed to offering all of our customers
the most relevant and up to date information about their
destination. To achieve that, we operate 90 localized websites in 41
languages. We have more than 25M customer reviews and more are
coming in every day, making a great candidate for machine
translation. Having evaluated Amazon Translate and several other
solutions, we believe that Amazon Translate presents a quick,
efficient and most importantly, accurate solution »
Matt Fryer, VP and Chief Data Science Officer, Hotels.com

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Amazon Transcribe
Automatic speech recognition service

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“Hello, this is Allan
speaking”
Automatic speech recognition service
Amazon
Transcribe

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Support for
telephony
audio
Timestamp
generation
Intelligent
punctuation
and formatting
Recognize
multiple
speakers
Custom
vocabulary
Multiple
languages
Automatic speech recognition service

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ringDNA
RingDNA is an end-to-end
communications platform for sales
teams.
Hundreds of enterprise organizations use
RingDNA to increase productivity, engage
in smarter sales conversations, gain
predictive sales insights and improve
their win rate.
Speech to Text
"A critical component of RingDNA’s Conversation
AI requires best of breed speech-to-text to deliver
transcriptions of every phone call. RingDNA is
excited about Amazon Transcribe since it provides
high-quality speech recognition at scale, helping
us to better transcribe every call to text"
Howard Brown, CEO & Founder, RingDNA
https://www.youtube.com/watch?v=1ZJ_f1bDdog

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Amazon Comprehend
Natural Language Processing

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Fully managed natural language processing
Discover valuable insights from text
Entities
Key Phrases
Language
Sentiment
Amazon
Comprehend

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Platform Services

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Data Visualization &
Analysis
Business Problem –
ML problem framing Data Collection
Data Integration
Data Preparation &
Cleaning
Feature Engineering
Model Training &
Parameter Tuning
Model Evaluation
Are Business
Goals met?
Model Deployment
Monitoring &
Debugging
– Predictions
YesNo
DataAugmentation
Feature
Augmentation
The Machine Learning Process
Re-training

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End-to-End
Machine Learning
Platform
Zero setup Flexible Model
Training
Pay by the second
$
Amazon SageMaker
Build, train, and deploy machine learning models at scale

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Highly-optimized
machine learning
algorithms
Deployment
without
engineering effort
Fully-managed
hosting at scale
BuildPre-built
notebook
instances
Deploy
Train
One-click training
for ML, DL, and
custom algorithms
Easier training with
hyperparameter
optimization
Amazon SageMaker

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Built-in ML Algorithm
https://docs.aws.amazon.com/sagemaker/latest/dg/algos.html
Problem Algorithm Learning Typ
Discrete Classification,
Regression
Linear Learner Supervised
XGBoost Algorithm Supervised
Discrete Recommendations Factorization Machines Supervised
Image Classification Image Classification Algorithm Supervised, CNN
Neural Machine Translation Sequence to Sequence Supervised, seq2seq
Time-series Prediction DeepAR Supervised, RNN
Discrete Groupings K-Means Algorithm Unsupervised
Dimensionality Reduction PCA (Principal Component Analysis) Unsupervised
Topic Determination Latent Dirichlet Allocation (LDA) Unsupervised
Neural Topic Model (NTM) Unsupervised,
Neural Network Based

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Digital Globe
http://blog.digitalglobe.com/industry/using-machine-learning-
to-save-money-on-cloud-data-storage/
https://www.youtube.com/watch?v=mkKkSRIxU8M
In the last 18 years DigitalGlobe
has been operating Earth imaging
satellites, they have collected over
100 PB of imagery.
There is a trade-off between how
quickly data can be accessed and
how much it will cost to store.
Working with the ML Lab, Digital
Globe built a predictive model that
will reduce cloud storage costs for
their imagery archive by 50%.

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Amazon ML Lab
Lots of companies
doing Machine
Learning
Unable to unlock
business potential
Brainstorming Modeling Teaching
Lack ML
expertise
Leverage Amazon experts with decades of ML
experience with technologies like Amazon Echo,
Amazon Alexa, Prime Air and Amazon Go
Amazon ML Lab
provides the missing
ML expertise

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Frameworks & Infrastructure

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Amazon EC2 P3 Instances
• Up to eight NVIDIA Tesla V100 GPUs
• 1 PetaFLOPs of computational
performance – 14x better than P2
• 300 GB/s GPU-to-GPU communication
(NVLink) – 9x better than P2
• 16GB GPU memory with 900 GB/sec peak
GPU memory bandwidth
T h e f a s t e s t , m o s t p o w e r f u l G P U i n s t a n c e s i n t h e c l o u d

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AWS Deep Learning AMI
• Easy-to-launch tutorials
• Hassle-free setup and configuration
• Pay only for what you use
• Accelerate your model training and deployment
• Support for popular deep learning frameworks

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Open Neural Network Exchange (ONNX)
• Developers can choose the framework that best fits their needs
• More customers can take advantage of MXNet’s performance and
scalability
• MXNet users to run their model on various mobile and edge devices
(Qualcomm, Huawei, Intel, and ARM announced support for ONNX)

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AWS DeepLens
Deep Learning enabled video camera
for developers

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A new way to learn
Custom built for deep learning
Broad Framework Support
Deploy models from Amazon SageMaker
Integrated with AWS
Full programmable with AWS Lambda
AWS DeepLens
W o r l d ’ s f i r s t D e e p L e a r n i n g e n a b l e d v i d e o c a m e r a f o r d e v e l o p e r s

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AWS DeepLens: Project Templates
Artistic Style Transfer Hot Dog/Not Hot
Dog Recognition
Object Recognition

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FRAMEWORKS AND INTERFACES
PLATFORM SERVICES
APPLICATION SERVICES
Amazon
Rekognition
Amazon
Polly
Amazon
Lex
Democratization of AI
Amazon
Rekognition
Video
Amazon
Transcribe
Amazon
Comprehend
Amazon
SageMaker
AWS DeepLens Amazon EMR
Deep Learning
AMI
Amazon
Translate

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Thank you!