Bagels & Bytes: Data Scientist Event
•
4 recomendaciones•501 vistas
An overview of Artificial Intelligence and Machine Learning on AWS Join us to gain an understanding of a spectrum of easy-to-use AWS Machine Learning services such as Amazon Recognition, Amazon Polly and Amazon Comprehend that rely on AWS pre-built Machine Learning models. In addition, hear how Amazon SageMaker allows Machine Learning practitioners to collaborate on building models using Jupyter notebooks. Craft custom Deep Learning algorithms using popular libraries such as TensorFlow, Keras, MXNet, or work with traditional Machine Learning algorithms such as XGBoost. You will also learn how to detect anomalies using Amazon Kinesis Analytics.
Recomendados
Recomendados
Más contenido relacionado
La actualidad más candente
La actualidad más candente (20)
Similar a Bagels & Bytes: Data Scientist Event
Similar a Bagels & Bytes: Data Scientist Event (20)
Más de Amazon Web Services
Más de Amazon Web Services (20)
Bagels & Bytes: Data Scientist Event
- 1. Data Scientists Event AI, Machine & Deep Learning By: Dan Vultur Enterprise Account Manager, Luxembourg
- 2. Application Services Platform Services Frameworks & Infrastructure Apache MXNet PyTorchCognitive Toolkit Keras Caffe2 & Caffe TensorFlow AWS Deep Learning AMI GPU MobileCPU IoT (Greengrass) Amazon Machine Learning Vision Speech Language Gluon AWS ML Stack SageMaker EMR Mechanical Turk
- 3. Application Services Platform Services Frameworks & Infrastructure Apache MXNet PyTorchCognitive Toolkit Keras Caffe2 & Caffe TensorFlow AWS Deep Learning AMI GPU MobileCPU IoT (Greengrass) Amazon Machine Learning Vision Speech Language Gluon AWS ML Stack SageMaker EMR Mechanical Turk
- 4. P3 Instances and AMI P2 P3 NVIDIA Tesla V100 GPUs 5,120 Tensor cores 128GB of memory ~14X faster than P2 P3 Instance 1 Petaflop of compute NVLink 2.0 AW S D e e p L e a r n i n g A M I
- 5. Deep learning frameworks KERAS I n t e r f a c e sF r a m e w o r k s
- 6. Application Services Platform Services Frameworks & Infrastructure Apache MXNet PyTorchCognitive Toolkit Keras Caffe2 & Caffe TensorFlow AWS Deep Learning AMI GPU MobileCPU IoT (Greengrass) Amazon Machine Learning Vision Speech Language Gluon AWS ML Stack SageMaker EMR Mechanical Turk
- 7. 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 Re-training The Machine Learning Process
- 8. 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 Re-training DataAugmentation The Machine Learning Process
- 9. Data Visualization & Analysis Feature Engineering Model Training & Parameter Tuning Model Evaluation • Setup and manage Notebook Environments • Setup and manage Training Clusters • Write Data Connectors • Scale ML algorithms to large datasets • Distribute ML training algorithm to multiple machines • Secure Model artifacts The Machine Learning Process
- 10. Business Problem – Model Deployment Monitoring & Debugging – Predictions • Setup and manage Model Inference Clusters • Manage and Scale Model Inference APIs • Monitor and Debug Model Predictions • Models versioning and performance tracking • Automate New Model version promotion to production (A/B testing) The Machine Learning Process
- 11. A fully managed service that enables data scientists and developers to quickly and easily build machine-learning based models into production smart applications. Amazon SageMaker
- 12. 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
- 14. Highly-optimized machine learning algorithms One-click training for ML, DL, and custom algorithms BuildPre-built notebook instances Easier training with hyperparameter optimization Train Amazon SageMaker
- 15. One-click training for ML, DL, and custom algorithms Easier training with hyperparameter optimization Highly-optimized machine learning algorithms Deployment without engineering effort Fully-managed hosting at scale BuildPre-built notebook instances Deploy Train Amazon SageMaker
- 16. Amazon SageMaker: Launch Customers
- 17. Amazon SageMaker: Launch Customers “With Amazon SageMaker, we can accelerate our Artificial Intelligence initiatives at scale by building and deploying our algorithms on the platform. We will create novel large-scale machine learning and AI algorithms and deploy them on this platform to solve complex problems that can power prosperity for our customers. " - Ashok Srivastava, Chief Data Officer, Intuit
- 18. Amazon SageMaker: Launch Customers “We’re focused on making it faster and easier than ever to hire and get hired, training our machine learning algorithms against hundreds of millions of historical transactional activities in order to deliver highly relevant job matches as quickly as possible. Amazon SageMaker provided us with an answer to problems we had with ML workflow management, allowing us to train, evaluate and deploy models in a flexible way. In addition, Amazon SageMaker's modularity provides the ability to build and create models independently, which is a compelling feature for ZipRecruiter. ” - Avi Golan, VP of Engineering, ZipRecruiter
- 19. Application Services Platform Services Frameworks & Infrastructure Apache MXNet PyTorchCognitive Toolkit Keras Caffe2 & Caffe TensorFlow AWS Deep Learning AMI GPU MobileCPU IoT (Greengrass) Amazon Machine Learning Vision Speech Language Gluon AWS ML Stack SageMaker EMR Mechanical Turk
- 20. Amazon Rekognition Potential Use Cases Searchable Image Library Detect Inappropriate Content in Images Face-based User Verification Sentiment Analysis Facial Recognition Celebrity Identification
- 21. Amazon Rekognition Video (GA) Analyze activity, recognize and track people in stored and live video stream Four primary capabilities 1. Person tracking 2. Facial recognition 3. Object and activity detection 4. Video streaming support Real-time and batch analysis Motion and time context
- 22. Amazon Rekognition Video (GA)
- 23. Amazon DeepLens DeepLens is a connected HD camera and developer kit that includes a set of sample projects to help developers learn machine learning concepts using hands- on computer vision use cases.
- 24. GET STARTED WITH SAMPLE PROJECTS ADD CUSTOM FUCTIONALITY OR CREATE YOUR OWN PROJECT ARTISTIC STYLE TRANSFER OBJECT DETECTION FACE DETECTION / RECOGNITION HOT DOG / NOT HOT DOG CAT VS. DOG ACTIVITY DETECTION
- 25. Application Services Platform Services Frameworks & Infrastructure Apache MXNet PyTorchCognitive Toolkit Keras Caffe2 & Caffe TensorFlow AWS Deep Learning AMI GPU MobileCPU IoT (Greengrass) Amazon Machine Learning Vision Speech Language Gluon AWS ML Stack SageMaker EMR Mechanical Turk
- 26. Amazon Polly Potential Use Cases Content Creation Education & E-learning Mobile & Desktop Applications Customer Contact Center Internet of Things (IoT) Accessibility
- 27. Amazon Transcribe A fu ll y m an ag e d an d co n t in u o u sly t rain e d au t o m at ic sp e e ch r e co g n it io n (A S R ) se r v ice t h at t ak e s in au dio an d au t o m at ical l y g e n e rat e s accu r at e t r an scr ip t s.
- 28. Amazon Transcribe: Automatic Speech Recognition (Preview) Timestamps & confidence scores Support for both regular & telephony audio Punctuation § S3 Integration Hello/ Hola English and Spanish with more to come Amazon S3
- 29. Amazon Transcribe: Automatic Speech Recognition (Preview) Detect Multiple Speakers Custom Vocabulary
- 30. Application Services Platform Services Frameworks & Infrastructure Apache MXNet PyTorchCognitive Toolkit Keras Caffe2 & Caffe TensorFlow AWS Deep Learning AMI GPU MobileCPU IoT (Greengrass) Amazon Machine Learning Vision Speech Language Gluon AWS ML Stack SageMaker EMR Mechanical Turk
- 31. Amazon Lex Potential Use Cases Appointment Booking Customer Support Informational Services Access Enterprise Data Internet of Things (IoT)
- 32. Amazon Translate Po w e r e d b y de e p- le ar n in g t e ch n o lo g ie s, A m az o n T ran sl at e is a t ran sl at io n se rv ice t h at de l iv e rs fast , h ig h - qu alit y , an d affo rdab le lan g u ag e t ran slat io n .
- 33. Product listings, descriptions;; search queries Website strings and functional content Cross-lingual communication: customer support, vendors and sellers Product documentation and support content I M M E N S E V O L U M E I N A D I V E R S E S E T O F U S E C A S E S K E Y T O G R O W T H A N D I N T E R N A T I O N A L E X P A N S I O N MACHINE TRANSLATION @ AMAZON
- 34. Any business that has customers who speak languages beyond the ones your business speaks today. WHO SHOULD USE THIS? Hello Hola Bonjour ﻣﺭرﺣﺑﺎ Hallo 你好 Olá ハロー नमस्ते
- 35. TRANSLATE ANY PLAIN TEXT INPUT REAL-TIME TRANSLATION 12 LANGUAGE PAIRS FOR PREVIEW LANGUAGE DETECTION PREVIEW FEATURES
- 36. Amazon Comprehend A m azo n C o m p r e h e n d is a Natu r al Lan g u ag e Pr o ce ssin g (NLP) e n g in e al l o w in g m ach in e s t o u n de rst an d t e xt . Ut il iz in g NLP, de v e l o p e rs can p e r fo rm t ask s su ch as se n tim e n t an d so cial m e dia an al y sis.
- 38. Amazon Comprehend – Use Cases A n a l y z i n g w h a t c u s t o m e r s a r e s a y i n g a b o u t y o u r b r a n d , p r o d u c t s , s e r v i c e s . M a k i n g s e a r c h s m a r t e r b y s e a r c h i n g o n k e y p h r a s e , s e n t i m e n t a n d t o p i c O r g a n i z i n g d o c u m e n t s , c a t e g o r i z i n g b y t o p i c a n d p e r s o n a l i z i n g e x p e r i e n c e s
- 39. Put machine learning in the hands of every developer and data scientist ML @ AWS: Our mission
- 40. Amazon ML Solutions 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
- 41. Amazon ML Lab Customers
- 42. Thank you! Learn more: https://pages.awscloud.com/AIWebinars.html Contact us: https://aws.amazon.com/contact-us