The document outlines the role of an AWS solutions architect specializing in machine learning and AI, detailing how they assist businesses in navigating AWS services and defining architectures. It emphasizes AWS's mission to make machine learning accessible to all developers and presents various tools and algorithms available in AWS for AI/ML. The discussion also highlights the importance of successful project implementation and the use of step functions to create automated workflows for machine learning projects.

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María Gaska AI/ML Solutions Architect
25/07/2019
Machine learning e IA @AWS
Webinar 2019

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Mi rol en AWS
Arquitecta de Soluciones
• Ayudar a navegar los servicios de
AWS
• Definir arquitecturas para resolver
problemas de negocios
Especialista en Machine Learning e
IA
• Discutir sobre algoritmos
(performance, monitoreo,
funcionamiento)
• Asesorar en soluciones de ML e
IA.

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F R A M E W O R K S E
I N F R A S T R U C T U R E
El stack para AI/ML de AWS
A I C O M O S E R V I C I O
R E K O G N I T I O N
I M A G E
P O L L Y T R A N S C R I B E T R A N S L A T E L E XR E K O G N I T I O N
V I D E O
Vision Speech Chatbots
M A C H I N E
L E A R N I N G
F r a m e w o r k s I n t e r f a c e s I n f r a s t r u c t u r e
E C 2 P 3
& P 3 d n
E C 2 C 5 F P G A s G R E E N G R A S S E L A S T I C
I N F E R E N C E
Language Forecasting Recommendations
T E X T R A C T
New
C O M P R E H E N D &
C O M P R E H E N D
M E D I C A L New
NewNew
F O R E C A S T P E R S O N A L I Z E
A M A Z O N
S A G E M A K E R
G R O U N D T R U T H
New
N O T E B O O K S M A R K E T P L A C E
New
A L G O R I T M O S
R E I N F O R C E M E N T
L E A R N I N G
New
T R A I N I N G
O P T I M I Z A T I O N
( N E O ) New
D E P L O Y
H O S T I N G

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Nuestra mission en AWS
Poner Machine Learning e IA en manos
de todos los desarrolladores

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Amazon SageMaker

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© 2017, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Machine Learning, un proceso complejo
Adquisición de
los datos
Limpieza
Preparaciœn y
transformación
EntrenamientoEvaluación
Integración,
deploy
Monitoreo
Data wrangling
• Desplegar ambientes
para de notebooks
• Llevar los datos hasta
las notebooks de forma
segura
Experimentación
• Manejo de clusters
• Escalar y/o distribuir
algoritmos de ML
Despliegue
• Set up y manejo de
clusters para
inferencia
• Manejar y
autoescalar APIs de
inferencia
• Testeo, versionado
y monitoreo

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© 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved.
Amazon SageMaker
1 2 3 5
I I I I
Notebook Instances
con 200+ Ejemplos
17 Algoritmos built-in ML Training Service Hosting de Servicios
4
I
Tuning de
hiperparámetros
1
1 + 𝑒𝑒−𝑥𝑥
6
Batch Transform
• Inferencia
• Transformación de
datos
7
SDK’s:
• Python
• Spark
8
Documentación
& White Papers
& Blog Posts

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Clasificación Computer Vision Topic Modeling
Trabajar con texto
Recomendación
Forecasting
• Linear Learner *
• XGBoost
• KNN
• Image Classification <>
• Blazing Text
• Supervised
• Unsupervised *
• Factorization
Machines *
• DeepAR *
• LDA
• NTM
Cada algoritmo resuelve un problema específico
Detección de anomalías
• Random Cut Forests *
Traducción de secuencias
• Seq2Seq *
• Object Detection <>
Clustering
• Kmeans *
Reducción de dimensiones
• PCARegresión
• Linear
Learner *
• XGBoost
• KNN
<> = incremental training
• IP Insights *
• Semantic Segmentation
• Object2Vec* = distributed training

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Implementación de modelos en
AWS

10. Implementación de modelos en AWS
Q Modelos
Productivos Frenados
“Según la encuesta de Alegion, el 78% de
los proyectos machine learning, se frenan
en algún punto anterior a la etapa de
implementación.”
– Business Wire, 23/05/2019

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https://github.com/githubmg/sagemaker-step-functions

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La herramienta apropiada para cada problema

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Construcción de un Workflow con Step Functions
Step Functions permite construer
un workflow que sincronice y
automatize la ejecución de cada
uno de los pasos de un proyecto
de machine learning productive.

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Q&AMaría Gaska
AI/ML Specialist, 2019

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Gracias!