SlideShare uma empresa Scribd logo
1 de 94
Baixar para ler offline
Machine Learning and TensorFlow
Artificial Intelligence Present and Future
José Papo
Gerente de relações com startups e developers
Google América Latina
@josepapo
“Machine learning is a core,
transformative way by which we’re
re-thinking how we’re doing everything”
Sundar Pichai
CEO, Google
“Machine learning will cause every
successful huge IPO win in 5 years.”
Eric Schmidt
Executive Chairman, Alphabet
Basic Concepts
● Artificial General Intelligence
● Artificial Superintelligence
● Artificial Narrow Intelligence
Artificial Intelligence
Machine Learning (Narrow AI)
Deep Learning (ML on Steroids!!!)
What’s different now from 10 years ago?
WAY MORE
DATA
More
Compute
Better
Algorithms
Machine Learning at Google
Products using Machine Learning
TensorFlow
● Open source Machine
Learning library
● Especially useful for
Deep Learning
● For research and
production
● Apache 2.0 license
Raspberry
Pi
DatacentersYour laptop Android iOS
Portable & Scalable
A multidimensional array.
A graph of operations.
Data Flow Graphs
Computation is defined as a directed acyclic graph
(DAG) to optimize an objective function
● Graph is defined in high-level language (Python)
● Graph is compiled and optimized
● Graph is executed (in parts or fully) on available low
level devices (CPU, GPU)
● Data (tensors) flow through the graph
● TensorFlow can compute gradients automatically
Image source: Wikimedia
+ =
A Neural Algorithm of Artistic Style http://arxiv.org/abs/1508.06576
?
Image source: Wikimedia
+ =
A Neural Algorithm of Artistic Style http://arxiv.org/abs/1508.06576
Image source: Wikimedia
+ =
A Neural Algorithm of Artistic Style http://arxiv.org/abs/1508.06576
goo.gl/fyDxhC
Most popular ML open source project on GitHub
Cloud, Mobile, Machine Learning
Cloud Machine Learning APIs
See, Hear and Understand the world
Cloud
Natural Language
Cloud
Speech
Cloud
Translate
Cloud
Vision
Faces
Faces, facial landmarks, emotions
OCR
Read and extract text, with
support for > 10 languages
Label
Detect entities from furniture to
transportation
Logos
Identify product logos
Landmarks & Image Properties
Detect landmarks & dominant
color of image
Safe Search
Detect explicit content - adult,
violent, medical and spoof
Cloud Vision API
Confidential & ProprietaryGoogle Cloud Platform 34
Cloud Natural Language API
Extract sentence, identify parts of
speech and create dependency parse
trees for each sentence.
Identify entities and label by types such
as person, organization, location, events,
products and media.
Understand the overall sentiment of a
block of text.
Syntax Analysis Entity Recognition
Sentiment Analysis
Confidential & ProprietaryGoogle Cloud Platform 35
Cloud Speech API
Automatic Speech Recognition (ASR)
powered by deep learning neural
networking to power your
applications like voice search or
speech transcription.
Recognizes over 80
languages and variants
with an extensive
vocabulary.
Returns partial
recognition results
immediately, as they
become available.
Filter inappropriate
content in text results.
Audio input can be captured by an application’s
microphone or sent from a pre-recorded audio
file. Multiple audio file formats are supported,
including FLAC, AMR, PCMU and linear-16.
Handles noisy audio from many
environments without requiring
additional noise cancellation.
Audio files can be uploaded in the
request and, in future releases,
integrated with Google Cloud
Storage.
Automatic Speech Recognition Global Vocabulary Inappropriate Content
Filtering
Streaming Recognition
Real-time or Buffered Audio Support Noisy Audio Handling Integrated API
Mobile Vision API
Providing on-device vision for applications
Face API
faces, facial landmarks, eyes
open, smiling
Barcode API
1D and 2D barcodes
Text API
Latin-based text / structure
Common Mobile Vision API
Support for fast image and video on-device detection and tracking.
NEW!
Face API
Photo credit developers.google.com/vision
Text Detection
Latin based language
Understand text structure
Photo credit Getty Images
Barcode Detection
1D barcodes
EAN-13/8
UPC-A/E
Code-39/93/128
ITF
Codabar
2D barcodes
QR Code
Data Matrix
PDF-417
AZTEC
UPC
DataMatrix
QR Code
PDF 417
Video and image credit Google
Machine Learning Democratization
Use Cases in Latin America
ACESSO UNIVERSAL A MEDICINA DE QUALIDADE
Machine Learning
AGENDA
• Otimização do broadcast
• Otimização do processo billing
• Personal Cloud
Machine
Learning
operacion
al
comercia
l
usuário
s
3perspectiva
s
Otimização do broadcast
• Reduzir a quantidade de envio de mensagens de
estímulo mantendo a mesma taxa de retorno.
comercia
l Desafio
Proposta
• Identificar o comportamento ou características dos
usuários mais propensos a responder ao estímulo.
Otimização do broadcast
• Text Mining para tratamento das frases,
classificando-as, como por exemplo, pela ideia
transmitida.
• Análise de modelos preditivos para seleção dos
clientes mais propensos.
comercia
l
Processo de
análise
Otimização do broadcast
• Prever quem não irá responder a nossa oferta nos
dá a possibilidade de pensarmos em algo diferente
para este usuário e desta forma conhecê-lo um
pouco mais.
• Redução de média 40% nos envios de broadcast.
comercia
l
Resultad
o
Otimização do billing
• Aumentar o sucesso nas cobranças dos serviços
prestados.
Desafi
o
Propost
a
• Identificar os clientes mais propensos em
determinados horários.
operacion
al
Otimização do billing
• Tratamento e enriquecimento da base de dados com
BigQuery.
• Análise de modelos preditivos para criação de escore de
crédito.
Processo de
análise
operacion
al
Otimização do billing
Proposição de
uso
Otimização do billing
• Redução de custos com infraestrutura de TI, uso
mais inteligente de recursos.
• Melhora de 42% em média na acertividade do
billing.
Resultad
o
operacion
al
Personal Cloud
• Detectar objetos e faces dentro das fotos dos
usuários do Personal Cloud para possibilitar busca e
criação de álbuns de forma automática
Desafi
o
Propost
a
• Utilização da API do Google Cloud Vision.
usuário
s
Busca por tags e álbuns
automáticos
Otimização do broadcast
Processo de
análiseusuário
s pé
dedo
bolsa
óculo
s
praia
Don’t Think Outside The
Box, Think Like There is NO
BOX!
tensorflow.org
github.com/tensorflow
Want to learn more?
Udacity class on Deep Learning, goo.gl/iHssII
Guides, codelabs, videos
MNIST for Beginners, goo.gl/tx8R2b
TF Learn Quickstart, goo.gl/uiefRn
TensorFlow for Poets, goo.gl/bVjFIL
ML Recipes, goo.gl/KewA03
TensorFlow and Deep Learning without a PhD, goo.gl/pHeXe7
Learn More...
OBRIGADO!
slideshare.net/jpapo
José Papo
@josepapo

Mais conteúdo relacionado

Mais procurados

Tensorflow London 13: Barbara Fusinska 'Hassle Free, Scalable, Machine Learni...
Tensorflow London 13: Barbara Fusinska 'Hassle Free, Scalable, Machine Learni...Tensorflow London 13: Barbara Fusinska 'Hassle Free, Scalable, Machine Learni...
Tensorflow London 13: Barbara Fusinska 'Hassle Free, Scalable, Machine Learni...
Seldon
 
Google Tech Talk with Dr. Eric Brewer in Korea Apr.27.2015
Google Tech Talk with Dr. Eric Brewer in Korea Apr.27.2015Google Tech Talk with Dr. Eric Brewer in Korea Apr.27.2015
Google Tech Talk with Dr. Eric Brewer in Korea Apr.27.2015
Chris Jang
 

Mais procurados (20)

[English] Create Mobile LBS Application Using Maps API
[English] Create Mobile LBS Application Using Maps API[English] Create Mobile LBS Application Using Maps API
[English] Create Mobile LBS Application Using Maps API
 
Cloud computing overview & Technical intro to Google Cloud
Cloud computing overview & Technical intro to Google CloudCloud computing overview & Technical intro to Google Cloud
Cloud computing overview & Technical intro to Google Cloud
 
Decode2018 report
Decode2018 reportDecode2018 report
Decode2018 report
 
GCP Gaming 2016 Keynote Seoul, Korea
GCP Gaming 2016 Keynote Seoul, KoreaGCP Gaming 2016 Keynote Seoul, Korea
GCP Gaming 2016 Keynote Seoul, Korea
 
Tensorflow London 13: Barbara Fusinska 'Hassle Free, Scalable, Machine Learni...
Tensorflow London 13: Barbara Fusinska 'Hassle Free, Scalable, Machine Learni...Tensorflow London 13: Barbara Fusinska 'Hassle Free, Scalable, Machine Learni...
Tensorflow London 13: Barbara Fusinska 'Hassle Free, Scalable, Machine Learni...
 
Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...
Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...
Kubeflow: portable and scalable machine learning using Jupyterhub and Kuberne...
 
Azure AI Conference Report
Azure AI Conference ReportAzure AI Conference Report
Azure AI Conference Report
 
Google Tech Talk with Dr. Eric Brewer in Korea Apr.27.2015
Google Tech Talk with Dr. Eric Brewer in Korea Apr.27.2015Google Tech Talk with Dr. Eric Brewer in Korea Apr.27.2015
Google Tech Talk with Dr. Eric Brewer in Korea Apr.27.2015
 
Introduction to gcp
Introduction to gcpIntroduction to gcp
Introduction to gcp
 
Google Developers Summit Tokyo - Google Cloud Platform で知る Google クラウドの「Googl...
Google Developers Summit Tokyo - Google Cloud Platform で知る Google クラウドの「Googl...Google Developers Summit Tokyo - Google Cloud Platform で知る Google クラウドの「Googl...
Google Developers Summit Tokyo - Google Cloud Platform で知る Google クラウドの「Googl...
 
Kaz Sato, Evangelist, Google at MLconf ATL 2016
Kaz Sato, Evangelist, Google at MLconf ATL 2016Kaz Sato, Evangelist, Google at MLconf ATL 2016
Kaz Sato, Evangelist, Google at MLconf ATL 2016
 
Google Cloud Platform - for Mobile Solutions
Google Cloud Platform - for Mobile SolutionsGoogle Cloud Platform - for Mobile Solutions
Google Cloud Platform - for Mobile Solutions
 
Scaling TensorFlow Models for Training using multi-GPUs & Google Cloud ML
Scaling TensorFlow Models for Training using multi-GPUs & Google Cloud MLScaling TensorFlow Models for Training using multi-GPUs & Google Cloud ML
Scaling TensorFlow Models for Training using multi-GPUs & Google Cloud ML
 
Distributed Deep Learning on Spark
Distributed Deep Learning on SparkDistributed Deep Learning on Spark
Distributed Deep Learning on Spark
 
GCP Gaming 2016 Seoul, Korea Gaming Analytics
GCP Gaming 2016 Seoul, Korea Gaming AnalyticsGCP Gaming 2016 Seoul, Korea Gaming Analytics
GCP Gaming 2016 Seoul, Korea Gaming Analytics
 
What's New in H2O Driverless AI? - Arno Candel - H2O AI World London 2018
What's New in H2O Driverless AI? - Arno Candel - H2O AI World London 2018What's New in H2O Driverless AI? - Arno Candel - H2O AI World London 2018
What's New in H2O Driverless AI? - Arno Candel - H2O AI World London 2018
 
Machine learning at scale by Amy Unruh from Google
Machine learning at scale by  Amy Unruh from GoogleMachine learning at scale by  Amy Unruh from Google
Machine learning at scale by Amy Unruh from Google
 
Big data on google cloud
Big data on google cloudBig data on google cloud
Big data on google cloud
 
Google Cloud Platform for Data Science teams
Google Cloud Platform for Data Science teamsGoogle Cloud Platform for Data Science teams
Google Cloud Platform for Data Science teams
 
CI/CD for Machine Learning with Daniel Kobran
CI/CD for Machine Learning with Daniel KobranCI/CD for Machine Learning with Daniel Kobran
CI/CD for Machine Learning with Daniel Kobran
 

Semelhante a Machine learning and TensorFlow

Semelhante a Machine learning and TensorFlow (20)

Initiate Edinburgh 2019 - Big Data Meets AI
Initiate Edinburgh 2019 - Big Data Meets AIInitiate Edinburgh 2019 - Big Data Meets AI
Initiate Edinburgh 2019 - Big Data Meets AI
 
IBM Cloud Artificial Intelligence : A Comprehensive Overview
IBM Cloud Artificial Intelligence : A Comprehensive OverviewIBM Cloud Artificial Intelligence : A Comprehensive Overview
IBM Cloud Artificial Intelligence : A Comprehensive Overview
 
Google Cloud: Data Analysis and Machine Learningn Technologies
Google Cloud: Data Analysis and Machine Learningn Technologies Google Cloud: Data Analysis and Machine Learningn Technologies
Google Cloud: Data Analysis and Machine Learningn Technologies
 
AWS Artificial Intelligence Day - Toronto
AWS Artificial Intelligence Day - TorontoAWS Artificial Intelligence Day - Toronto
AWS Artificial Intelligence Day - Toronto
 
Amazon Web Services - Strategy and Current Offering
Amazon Web Services - Strategy and Current OfferingAmazon Web Services - Strategy and Current Offering
Amazon Web Services - Strategy and Current Offering
 
Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...
Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...
Google Analytics Konferenz 2018_Machine Learning / AI mit Google_Lukman Ramse...
 
Python
PythonPython
Python
 
Unlocking New Todays: Artificial Intelligence and Data Platforms on AWS
Unlocking New Todays: Artificial Intelligence and Data Platforms on AWSUnlocking New Todays: Artificial Intelligence and Data Platforms on AWS
Unlocking New Todays: Artificial Intelligence and Data Platforms on AWS
 
How Amazon AI Can Help You Transform Your Education Business | AWS Webinar
How Amazon AI Can Help You Transform Your Education Business | AWS WebinarHow Amazon AI Can Help You Transform Your Education Business | AWS Webinar
How Amazon AI Can Help You Transform Your Education Business | AWS Webinar
 
Microsoft + OpenAI: Recent Updates (Machine Learning 15minutes! Broadcast #74)
Microsoft + OpenAI: Recent Updates (Machine Learning 15minutes! Broadcast #74)Microsoft + OpenAI: Recent Updates (Machine Learning 15minutes! Broadcast #74)
Microsoft + OpenAI: Recent Updates (Machine Learning 15minutes! Broadcast #74)
 
TechDayPakistan-Slides RAG with Cosmos DB.pptx
TechDayPakistan-Slides RAG with Cosmos DB.pptxTechDayPakistan-Slides RAG with Cosmos DB.pptx
TechDayPakistan-Slides RAG with Cosmos DB.pptx
 
Startup Village Keynote 2020
Startup Village Keynote 2020Startup Village Keynote 2020
Startup Village Keynote 2020
 
Bagels & Bytes: Data Scientist Event
Bagels & Bytes: Data Scientist EventBagels & Bytes: Data Scientist Event
Bagels & Bytes: Data Scientist Event
 
Big Data LDN 2017: Applied AI using Cognitive Services
Big Data LDN 2017: Applied AI using Cognitive ServicesBig Data LDN 2017: Applied AI using Cognitive Services
Big Data LDN 2017: Applied AI using Cognitive Services
 
SDSC18 and DSATL Meetup March 2018
SDSC18 and DSATL Meetup March 2018 SDSC18 and DSATL Meetup March 2018
SDSC18 and DSATL Meetup March 2018
 
Ai/ML services
Ai/ML servicesAi/ML services
Ai/ML services
 
AI and Innovations on AWS
AI and Innovations on AWSAI and Innovations on AWS
AI and Innovations on AWS
 
Google Cloud Platform - Cloud-Native Roadshow Stuttgart
Google Cloud Platform - Cloud-Native Roadshow StuttgartGoogle Cloud Platform - Cloud-Native Roadshow Stuttgart
Google Cloud Platform - Cloud-Native Roadshow Stuttgart
 
Google Cloud Platform Munich
Google Cloud Platform MunichGoogle Cloud Platform Munich
Google Cloud Platform Munich
 
Chatbots: Automated Conversational Model using Machine Learning
Chatbots: Automated Conversational Model using Machine LearningChatbots: Automated Conversational Model using Machine Learning
Chatbots: Automated Conversational Model using Machine Learning
 

Mais de Jose Papo, MSc

Mais de Jose Papo, MSc (20)

Machine Learning e AI - O que o Google oferece
Machine Learning e AI - O que o Google ofereceMachine Learning e AI - O que o Google oferece
Machine Learning e AI - O que o Google oferece
 
Por que o Google Cloud Platform é diferente
Por que o Google Cloud Platform é diferentePor que o Google Cloud Platform é diferente
Por que o Google Cloud Platform é diferente
 
Serverless: Um novo paradigma de arquitetura de aplicações - Exemplos com Fir...
Serverless: Um novo paradigma de arquitetura de aplicações - Exemplos com Fir...Serverless: Um novo paradigma de arquitetura de aplicações - Exemplos com Fir...
Serverless: Um novo paradigma de arquitetura de aplicações - Exemplos com Fir...
 
Introdução ao Firebase
Introdução ao FirebaseIntrodução ao Firebase
Introdução ao Firebase
 
Ferramentas e programas do Google para startups e apps
Ferramentas e programas do Google para startups e appsFerramentas e programas do Google para startups e apps
Ferramentas e programas do Google para startups e apps
 
As 8 características de um gestor e líder no "Estilo Google"
As 8 características de um gestor e líder no "Estilo Google"As 8 características de um gestor e líder no "Estilo Google"
As 8 características de um gestor e líder no "Estilo Google"
 
The Hyper Connected Era: Mobile First, Cloud First and Multi Screen
The Hyper Connected Era: Mobile First, Cloud First and Multi Screen The Hyper Connected Era: Mobile First, Cloud First and Multi Screen
The Hyper Connected Era: Mobile First, Cloud First and Multi Screen
 
Mobile, UX e Micro-momentos
Mobile, UX e Micro-momentosMobile, UX e Micro-momentos
Mobile, UX e Micro-momentos
 
Cloud Computing: De tendencia a realidade
Cloud Computing: De tendencia a realidadeCloud Computing: De tendencia a realidade
Cloud Computing: De tendencia a realidade
 
Novidades do Google IO 2015
Novidades do Google IO 2015Novidades do Google IO 2015
Novidades do Google IO 2015
 
Opções de Backends para seus apps móveis: Análise e Arquiteturas
Opções de Backends para seus apps móveis: Análise e ArquiteturasOpções de Backends para seus apps móveis: Análise e Arquiteturas
Opções de Backends para seus apps móveis: Análise e Arquiteturas
 
A Nova Era Hiper Conectada: Mobile-First, Cloud-First e Multi-Screen
A Nova Era Hiper Conectada: Mobile-First, Cloud-First e Multi-ScreenA Nova Era Hiper Conectada: Mobile-First, Cloud-First e Multi-Screen
A Nova Era Hiper Conectada: Mobile-First, Cloud-First e Multi-Screen
 
Como organizar e definir ritmo em sua startup/empresa "Google Style"
Como organizar e definir ritmo em sua startup/empresa "Google Style"Como organizar e definir ritmo em sua startup/empresa "Google Style"
Como organizar e definir ritmo em sua startup/empresa "Google Style"
 
Google BigQuery - Introdução
Google BigQuery - IntroduçãoGoogle BigQuery - Introdução
Google BigQuery - Introdução
 
Novidades do Google I/O 2014 - Uma Visão
Novidades do Google I/O 2014 - Uma VisãoNovidades do Google I/O 2014 - Uma Visão
Novidades do Google I/O 2014 - Uma Visão
 
Introdução ao Google Cloud Platform: Computação em Nuvem do Google
Introdução ao Google Cloud Platform: Computação em Nuvem do GoogleIntrodução ao Google Cloud Platform: Computação em Nuvem do Google
Introdução ao Google Cloud Platform: Computação em Nuvem do Google
 
Introdução ao pitch de ouro
Introdução ao pitch de ouroIntrodução ao pitch de ouro
Introdução ao pitch de ouro
 
Monetizacao e Hipoteses orientadas a objetivos
Monetizacao e Hipoteses orientadas a objetivosMonetizacao e Hipoteses orientadas a objetivos
Monetizacao e Hipoteses orientadas a objetivos
 
A Nova Era Industrial: Internet das Coisas e como escalar uma startup de hard...
A Nova Era Industrial: Internet das Coisas e como escalar uma startup de hard...A Nova Era Industrial: Internet das Coisas e como escalar uma startup de hard...
A Nova Era Industrial: Internet das Coisas e como escalar uma startup de hard...
 
Gato ou gado? Como você trata seus servidores?
Gato ou gado? Como você trata seus servidores?Gato ou gado? Como você trata seus servidores?
Gato ou gado? Como você trata seus servidores?
 

Último

Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
panagenda
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
WSO2
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Último (20)

Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost SavingRepurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
Repurposing LNG terminals for Hydrogen Ammonia: Feasibility and Cost Saving
 
Why Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire businessWhy Teams call analytics are critical to your entire business
Why Teams call analytics are critical to your entire business
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : UncertaintyArtificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
 
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 AmsterdamDEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
DEV meet-up UiPath Document Understanding May 7 2024 Amsterdam
 
CNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In PakistanCNIC Information System with Pakdata Cf In Pakistan
CNIC Information System with Pakdata Cf In Pakistan
 
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemkeProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
Web Form Automation for Bonterra Impact Management (fka Social Solutions Apri...
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
 
Ransomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdfRansomware_Q4_2023. The report. [EN].pdf
Ransomware_Q4_2023. The report. [EN].pdf
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf[BuildWithAI] Introduction to Gemini.pdf
[BuildWithAI] Introduction to Gemini.pdf
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 

Machine learning and TensorFlow

  • 1. Machine Learning and TensorFlow Artificial Intelligence Present and Future José Papo Gerente de relações com startups e developers Google América Latina @josepapo
  • 2.
  • 3. “Machine learning is a core, transformative way by which we’re re-thinking how we’re doing everything” Sundar Pichai CEO, Google
  • 4. “Machine learning will cause every successful huge IPO win in 5 years.” Eric Schmidt Executive Chairman, Alphabet
  • 6. ● Artificial General Intelligence ● Artificial Superintelligence ● Artificial Narrow Intelligence Artificial Intelligence
  • 8. Deep Learning (ML on Steroids!!!)
  • 9.
  • 10. What’s different now from 10 years ago? WAY MORE DATA More Compute Better Algorithms
  • 11.
  • 14.
  • 15.
  • 16.
  • 17.
  • 18.
  • 20.
  • 21. ● Open source Machine Learning library ● Especially useful for Deep Learning ● For research and production ● Apache 2.0 license
  • 23. A multidimensional array. A graph of operations.
  • 24. Data Flow Graphs Computation is defined as a directed acyclic graph (DAG) to optimize an objective function ● Graph is defined in high-level language (Python) ● Graph is compiled and optimized ● Graph is executed (in parts or fully) on available low level devices (CPU, GPU) ● Data (tensors) flow through the graph ● TensorFlow can compute gradients automatically
  • 25.
  • 26. Image source: Wikimedia + = A Neural Algorithm of Artistic Style http://arxiv.org/abs/1508.06576 ?
  • 27. Image source: Wikimedia + = A Neural Algorithm of Artistic Style http://arxiv.org/abs/1508.06576
  • 28. Image source: Wikimedia + = A Neural Algorithm of Artistic Style http://arxiv.org/abs/1508.06576 goo.gl/fyDxhC
  • 29. Most popular ML open source project on GitHub
  • 31. Cloud Machine Learning APIs See, Hear and Understand the world
  • 33. Faces Faces, facial landmarks, emotions OCR Read and extract text, with support for > 10 languages Label Detect entities from furniture to transportation Logos Identify product logos Landmarks & Image Properties Detect landmarks & dominant color of image Safe Search Detect explicit content - adult, violent, medical and spoof Cloud Vision API
  • 34. Confidential & ProprietaryGoogle Cloud Platform 34 Cloud Natural Language API Extract sentence, identify parts of speech and create dependency parse trees for each sentence. Identify entities and label by types such as person, organization, location, events, products and media. Understand the overall sentiment of a block of text. Syntax Analysis Entity Recognition Sentiment Analysis
  • 35. Confidential & ProprietaryGoogle Cloud Platform 35 Cloud Speech API Automatic Speech Recognition (ASR) powered by deep learning neural networking to power your applications like voice search or speech transcription. Recognizes over 80 languages and variants with an extensive vocabulary. Returns partial recognition results immediately, as they become available. Filter inappropriate content in text results. Audio input can be captured by an application’s microphone or sent from a pre-recorded audio file. Multiple audio file formats are supported, including FLAC, AMR, PCMU and linear-16. Handles noisy audio from many environments without requiring additional noise cancellation. Audio files can be uploaded in the request and, in future releases, integrated with Google Cloud Storage. Automatic Speech Recognition Global Vocabulary Inappropriate Content Filtering Streaming Recognition Real-time or Buffered Audio Support Noisy Audio Handling Integrated API
  • 36. Mobile Vision API Providing on-device vision for applications
  • 37. Face API faces, facial landmarks, eyes open, smiling Barcode API 1D and 2D barcodes Text API Latin-based text / structure Common Mobile Vision API Support for fast image and video on-device detection and tracking. NEW!
  • 38. Face API Photo credit developers.google.com/vision
  • 39. Text Detection Latin based language Understand text structure Photo credit Getty Images
  • 40. Barcode Detection 1D barcodes EAN-13/8 UPC-A/E Code-39/93/128 ITF Codabar 2D barcodes QR Code Data Matrix PDF-417 AZTEC UPC DataMatrix QR Code PDF 417 Video and image credit Google
  • 41. Machine Learning Democratization Use Cases in Latin America
  • 42.
  • 43.
  • 44.
  • 45.
  • 46.
  • 47.
  • 48.
  • 49.
  • 50.
  • 51.
  • 52.
  • 53.
  • 54.
  • 55.
  • 56.
  • 57.
  • 58. ACESSO UNIVERSAL A MEDICINA DE QUALIDADE
  • 60. AGENDA • Otimização do broadcast • Otimização do processo billing • Personal Cloud Machine Learning
  • 62. Otimização do broadcast • Reduzir a quantidade de envio de mensagens de estímulo mantendo a mesma taxa de retorno. comercia l Desafio Proposta • Identificar o comportamento ou características dos usuários mais propensos a responder ao estímulo.
  • 63. Otimização do broadcast • Text Mining para tratamento das frases, classificando-as, como por exemplo, pela ideia transmitida. • Análise de modelos preditivos para seleção dos clientes mais propensos. comercia l Processo de análise
  • 64. Otimização do broadcast • Prever quem não irá responder a nossa oferta nos dá a possibilidade de pensarmos em algo diferente para este usuário e desta forma conhecê-lo um pouco mais. • Redução de média 40% nos envios de broadcast. comercia l Resultad o
  • 65. Otimização do billing • Aumentar o sucesso nas cobranças dos serviços prestados. Desafi o Propost a • Identificar os clientes mais propensos em determinados horários. operacion al
  • 66. Otimização do billing • Tratamento e enriquecimento da base de dados com BigQuery. • Análise de modelos preditivos para criação de escore de crédito. Processo de análise operacion al
  • 68. Otimização do billing • Redução de custos com infraestrutura de TI, uso mais inteligente de recursos. • Melhora de 42% em média na acertividade do billing. Resultad o operacion al
  • 69. Personal Cloud • Detectar objetos e faces dentro das fotos dos usuários do Personal Cloud para possibilitar busca e criação de álbuns de forma automática Desafi o Propost a • Utilização da API do Google Cloud Vision. usuário s Busca por tags e álbuns automáticos
  • 70. Otimização do broadcast Processo de análiseusuário s pé dedo bolsa óculo s praia
  • 71. Don’t Think Outside The Box, Think Like There is NO BOX!
  • 72.
  • 73.
  • 74.
  • 75.
  • 76.
  • 77.
  • 78.
  • 79.
  • 80.
  • 81.
  • 82.
  • 83.
  • 84.
  • 85.
  • 86.
  • 87.
  • 88.
  • 89.
  • 90.
  • 91.
  • 92.
  • 93. tensorflow.org github.com/tensorflow Want to learn more? Udacity class on Deep Learning, goo.gl/iHssII Guides, codelabs, videos MNIST for Beginners, goo.gl/tx8R2b TF Learn Quickstart, goo.gl/uiefRn TensorFlow for Poets, goo.gl/bVjFIL ML Recipes, goo.gl/KewA03 TensorFlow and Deep Learning without a PhD, goo.gl/pHeXe7 Learn More...