Machine Learning in Finance: Moving forward!

Self-Driving cars. Commercial drones. Smart cameras. Movie and music creation. Powerful & intelligent robots. Over the past few years, a new revolution has brought AI almost to the level of science-fiction. However, most companies are not worried about far-off futuristic applications of AI, they want to know what AI can do - today - for their organizations. Distinguishing the hype from reality can be a bit confusing, especially when you consider the attention that AI gets from the media and commentators. So, how can your organization get started and put AI to work for you? That is the question I will answer in this talk. From greater customer intimacy, increasing competitive advantage and improving efficiency, I will discuss and show how AI can be used today and help the organization in more impact-full ways.

Transcript

1. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Adrian Hornsby Sr. Technical Evangelist | Amazon Web Services Machine Learning in Finance: Moving forward! @adhorn
2. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Myth: ML is dark magic
3. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark What are we talking about? AI RL DL Machine Learning
4. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark One of the ”Founding Father" of Artificial Intelligence John McCarthy 1955
5. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Photo from the 1956 Dartmouth Conference with Marvin Minsky, Ray Solomonoff, Claude Shannon, John McCarthy, Trenchard More, Oliver Selfridge and Nathaniel Rawchester
6. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Frank Rosenblatt, 1957 Perceptron
7. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Robert Schlaifer, 1959 Bayesian Decision Theory
8. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark First known deep network Alexey Grigorevich Ivakhnenko, 1965 Image of Prof. Alexey Ivakhnenko courtesy of Wikipedia.
9. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark 1969 First financial application
10. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Paul Werbos, 1975 Backpropagation
11. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Protrader expert system by K.C Chen and Ting-peng Lian Chen and Lian were able to predict the 87 point drop in Dow Jones Industrial Average in 1986
12. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark LeCun, 1989 First application of backpropagation https://www.youtube.com/watch?v=FwFduRA_L6Q
13. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Expert System Development – 90’s • PlanPower & Client Profiling System created by Applied Expert Systems • providing tailored financial plans • Chase Lincoln First Bank and Arthur D. Little Inc. • investment & debt planning • retirement & life-insurance planning • budget recommendations, • income tax planning and savings achievement • U.S Department of Treasury created FinCEN Artificial Intelligence system. • money laundering.
14. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark The curse of dimensionality
15. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark The Advent of ML – 2000’s Digital Data GPUs & Acceleration Cloud Computing Algorithms
16. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Explosion in AI and ML Use Cases Image recognition and tagging for photo organization Object detection, tracking and navigation for Autonomous Vehicles Speech recognition & synthesis in Intelligent Voice Assistants Algorithmic trading strategy performance improvement Sentiment analysis for targeted advertisements
17. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark The Amazon ML stack A I S E R V I C E S M L S E R V I C E S M L F R A M E W O R K S & I N F R A S T R U C T U R E A m a z o n S a g e Ma k e r G r o u n d T r u t h A l g o r i t h m s N o t e b o o k s M a r k e t p l a c e U n s u p e r v i s e d L e a r n i n g S u p e r v i s e d L e a r n i n g R e i n f o r c e m e n t L e a r n i n g O p t i m i z a t i o n ( N e o ) T r a i n i n g H o s t i n g D e p l o y m e n t Frameworks Interfaces Infrastructure A m a z o n R e k o g n i t i o n I m a g e A m a z o n P o l l y A m a z o n T r a n s c r i b e A m a z o n T r a n s l a t e A m a z o n C o m p r e h e n d A m a z o n L e x A m a z o n R e k o g n i t i o n V i d e o Vision Speech Language Chatbots A m a z o n F o r e c a s t Forecasting A m a z o n T e x t r a c t A m a z o n p e r s o n a l i z e Recommendations A m a z o n E C 2 P 3 & P 3 D N A m a z o n E C 2 C 5 F P G A s A W S G r e e n g r a s s A m a z o n E l a s t i c I n f e r e n c e A m a z o n I n f e r e n t i a
18. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark More machine learning happens on AWS
19. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark We all want machine learning everywhere
20. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Supervised learning Run an algorithm on a labelled data set, i.e. a data set containing samples and answers. Gradually, the model learns how to correctly predict the right answer. Regression and classification are examples of supervised learning. Unsupervised learning Run an algorithm on an unlabelled data set, i.e. a data set containing samples only. Here, the model progressively learns patterns in data and organizes samples accordingly. Clustering and topic modeling are examples of unsupervised learning. Types of Machine Learning
21. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Supervised learning Unsupervised learning SOPHISTICATION OF ML MODELS AMOUNT OF TRAINING DATA REQUIRED Types of Machine Learning
22. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark AMOUNT OF TRAINING DATA REQUIRED Supervised learning Unsupervised learning SOPHISTICATION OF ML MODELS Types of Machine Learning
23. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Reinforcement learning (RL) Supervised learning Unsupervised learning AMOUNT OF TRAINING DATA REQUIRED SOPHISTICATION OF ML MODELS Types of Machine Learning
24. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Remember when you first learned this?
25. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Let’s start with Deep Learning?
26. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Predicting the price of a house with humans Price City ZipCode Life Quality Parking Size # Room Accessibility Family Friendly
27. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Predicting the price of a house with neural net Price City ZipCode Life Quality Parking Size # Room Accessibility Family Friendly Input Output Discovered by the neural network
28. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Deep Learning Training Dataset The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. Human-in-the-loop
29. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://ml4a.github.io/ml4a/neural_networks/ Deep Learning Training
30. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://ml4a.github.io/ml4a/neural_networks/ Learning Deep Learning Training
31. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Learning = Minimizing the loss (error) function Backpropagation
32. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Early stopping Training accuracy Loss function Accuracy 100% Epochs Validation accuracy Loss Best epoch OVERFITTING
33. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Deep Learning is a big deal It’s able to do better than other ML and Humans
34. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Convolutional Neural Networks (CNN) Conv 1 Conv 2 Conv n … … Feature Maps Labrador Dog Beach Outdoors Softmax Probability Fully Connected Layer
35. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://github.com/precedenceguo/mx-rcnn https://github.com/zhreshold/mxnet-yolo CNN: Object Detection
36. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark CNN: Object Detection
37. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark CNN: Object Segmentation
38. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark CNN: Text Detection and Recognition https://github.com/Bartzi/stn-ocr
39. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://github.com/tornadomeet/mxnet-face CNN: Face Detection
40. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark FDA-approved medical imaging https://www.periscope.tv/AWSstartups/1vAGRgevBXRJl https://www.youtube.com/watch?v=WE81dncwnIc CNN: Object Segmentation
41. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark CNN: Real-Time Pose Estimation https://github.com/dragonfly90/mxnet_Realtime_Multi-Person_Pose_Estimation
42. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark CapsNet: Capsule Networks Spatial Memory https://medium.com/ai%C2%B3-theory-practice-business/understanding-hintons-capsule-networks-part-i-intuition-b4b559d1159b
43. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Long Short Term Memory Networks (LSTM) Oh I remember! https://github.com/awslabs/sockeye
44. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark PredNet: Prediction Networks What comes next https://coxlab.github.io/prednet/
45. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Generative Adversarial Networks (GAN) The future at work (already) today Generating new ”celebrity” faces https://github.com/tkarras/progressive_growing_of_gans
46. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Generative adversarial networks (GAN) The future at work (already) today Semantic labels → Cityscapes street views https://tcwang0509.github.io/pix2pixHD/
47. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Wait! There’s more! Models can also generate text from text, text from images, text from video, images from text, sound from video, 3D models from 2D images, etc.
48. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark How do people ”build” Neural Nets?
49. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark 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 Yes No Data Augmentation Feature Augmentation The ML Process Re-training Predictions
50. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark AI/ML Workflow Performance monitoring & adaptation 8 Data Acquisition & Storage 1 Model & Framework selection 3 Model Training 4 Hyper parameter tuning 5 Model testing and simulation 6 Model Deployment (inference) 7 Data Labelling 2
51. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Model Zoos & Transfer Learning • Full implementations of many state-of-the-art models reported in the academic literature. • Complete models, with scripts, pre-trained weights and instructions on how to build and fine tune these models.
52. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://mxnet.apache.org/model_zoo/index.html
53. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Transfer Learning (hidden gem) • Initialize parameter with pre-trained model • Use pre-trained model as fixed feature extractor and build model based on feature • Why? It takes a long time and a lot of resources to train a neural network from scratch.
54. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark https://www.youtube.com/watch?v=qGotULKg8e0 • Over 10 million images from 300,000 hotels • Fine-tuned a pre-trained CNN using 100,000 images • Hotel descriptions now automatically feature the best available images Ranking Hotel Images Using Transfer Learning https://news.developer.nvidia.com/expedia-ranking-hotel-images-with-deep-learning/
55. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Let’s talk about Reinforcement Learning (RL)
56. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Defining Reinforcement Learning Source: Wikipedia
57. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark The players Simulation environment RL agent SageMaker Training R O L L O U T Initial model
58. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark At first, it can’t even stand up
59. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Actions and observations Simulation environment Actions Observation RL agent Initial model SageMaker Training R O L L O U T
60. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark The model learns through actions and observations
61. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Interactions in the environment generate training data Simulation environment Actions Observation RL agent Training Data Observation, action, reward SageMaker Training
62. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Training results in model updates Simulation environment Actions Observation RL agent Model updates Training data Observation, action, reward SageMaker Training
63. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Harry learns to stand and step
64. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Making progress
65. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark RL agents try to maximize rewards
66. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Eventually, the model learns how to walk and run You can continue training Harry to jump obstacles, play games, dance, and more
67. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark This makes RL applicable in many domains and not just gaming
68. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Financial portfolio management Objective Maximize value of a financial portfolio S TAT E Current stock portfolio, price history A C T I O N Buy, sell stocks R E W A R D Positive when return is positive Negative when return is negative
69. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Vehicle routing Objective Fulfill customer orders S TAT E Current location, distance from homes … A C T I O N Accept, pick up, and deliver order R E WA R D Positive when we deliver on time Negative when we fail to deliver on time
70. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Autoscaling Objective Adapt instance capacity to load profile S TAT E Current load, failed jobs, active machines A C T I O N Remove or add machines R E W A R D Positive for successful transactions High penalty for losing transactions
71. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark The Amazon ML stack A I S E R V I C E S M L S E R V I C E S M L F R A M E W O R K S & I N F R A S T R U C T U R E A m a z o n S a g e Ma k e r G r o u n d T r u t h A l g o r i t h m s N o t e b o o k s M a r k e t p l a c e U n s u p e r v i s e d L e a r n i n g S u p e r v i s e d L e a r n i n g R e i n f o r c e m e n t L e a r n i n g O p t i m i z a t i o n ( N e o ) T r a i n i n g H o s t i n g D e p l o y m e n t Frameworks Interfaces Infrastructure A m a z o n R e k o g n i t i o n I m a g e A m a z o n P o l l y A m a z o n T r a n s c r i b e A m a z o n T r a n s l a t e A m a z o n C o m p r e h e n d A m a z o n L e x A m a z o n R e k o g n i t i o n V i d e o Vision Speech Language Chatbots A m a z o n F o r e c a s t Forecasting A m a z o n T e x t r a c t A m a z o n p e r s o n a l i z e Recommendations A m a z o n E C 2 P 3 & P 3 D N A m a z o n E C 2 C 5 F P G A s A W S G r e e n g r a s s A m a z o n E l a s t i c I n f e r e n c e A m a z o n I n f e r e n t i a
72. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Where do you start? The Low Hanging Fruits
73. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark The Amazon ML stack A I S E R V I C E S M L S E R V I C E S M L F R A M E W O R K S & I N F R A S T R U C T U R E A m a z o n S a g e Ma k e r G r o u n d T r u t h A l g o r i t h m s N o t e b o o k s M a r k e t p l a c e U n s u p e r v i s e d L e a r n i n g S u p e r v i s e d L e a r n i n g R e i n f o r c e m e n t L e a r n i n g O p t i m i z a t i o n ( N e o ) T r a i n i n g H o s t i n g D e p l o y m e n t Frameworks Interfaces Infrastructure A m a z o n R e k o g n i t i o n I m a g e A m a z o n P o l l y A m a z o n T r a n s c r i b e A m a z o n T r a n s l a t e A m a z o n C o m p r e h e n d A m a z o n L e x A m a z o n R e k o g n i t i o n V i d e o Vision Speech Language Chatbots A m a z o n F o r e c a s t Forecasting A m a z o n T e x t r a c t A m a z o n p e r s o n a l i z e Recommendations A m a z o n E C 2 P 3 & P 3 D N A m a z o n E C 2 C 5 F P G A s A W S G r e e n g r a s s A m a z o n E l a s t i c I n f e r e n c e A m a z o n I n f e r e n t i a
74. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Amazon Rekognition Deep learning-based image & video analysis
75. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark http://timescapes.org/trailers/
76. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
77. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Amazon Polly “What's the difference between a hippo and a zippo? One is really heavy, and the other is a little lighter.” Amazon Polly: Text In, Life-like Speech Out The Text-To-Speech technology behind Amazon Polly takes advantage of bidirectional long short-term memory (LSTM)* 52 voices across 25 languages
78. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark <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
79. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark “With Amazon Polly our users benefit from the most lifelike Text-to-Speech voices available on the market.” Severin Hacker CTO, Duolingo
80. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Amazon Comprehend Discover insights from text Entities Key Phrases Language Sentiment Amazon Comprehend Topic Modeling
81. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark
82. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark « Amazon Comprehend helps us analyze the key sentiments, objects, and geos in our 30 million plus reviews & testimonies […] so our customers can make the best decision possible for their travel.” Matt Fryer, VP and Chief Data Science Officer Hotels.com https://aws.amazon.com/solutions/case-studies/expedia/
83. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Amazon Forecast Accurate time-series forecasting service, based on the same technology used at Amazon.com. No ML experience required. NEW
84. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Historical data Sales, inventory, pricing, etc. Related data Weather, competitive promotions, etc. 1. Load data 2. Inspect data 3. Identify features 4. Select algorithms 5. Select hyperparameters 6. Train models 7. Optimize models 8. Deploy and host models Amazon Forecast Customized Forecasting API Private
85. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Sample use cases Product demand Workforce demand Financial metrics Inventory planning
86. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Amazon Personalize Real-time personalization and recommendation service, based on the same technology used at Amazon.com. No ML experience required. NEW
87. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Real-time data can be consumed by Amazon Personalize Historical user activity User attributes Item catalog Real-time data Mobile SDKs (coming soon) JavaScript SDK Amazon S3 bucket Server-Side SDKs Offline data
88. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Activity stream Views, signups, conversion, etc. Inventory Videos, products, articles, etc. Customized Personalization API Demographics (optional) Name, age, location, etc. 1. Load data 2. Inspect data 3. Identify features 4. Select algorithms 5. Select hyperparameters 6. Train models 7. Optimize models 8. Build feature store 9. Deploy and host models 10.Create real-time caches Amazon Personalize
89. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark More machine learning happens on AWS
90. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark The Amazon ML stack A I S E R V I C E S M L S E R V I C E S M L F R A M E W O R K S & I N F R A S T R U C T U R E A m a z o n S a g e Ma k e r G r o u n d T r u t h A l g o r i t h m s N o t e b o o k s M a r k e t p l a c e U n s u p e r v i s e d L e a r n i n g S u p e r v i s e d L e a r n i n g R e i n f o r c e m e n t L e a r n i n g O p t i m i z a t i o n ( N e o ) T r a i n i n g H o s t i n g D e p l o y m e n t Frameworks Interfaces Infrastructure A m a z o n R e k o g n i t i o n I m a g e A m a z o n P o l l y A m a z o n T r a n s c r i b e A m a z o n T r a n s l a t e A m a z o n C o m p r e h e n d A m a z o n L e x A m a z o n R e k o g n i t i o n V i d e o Vision Speech Language Chatbots A m a z o n F o r e c a s t Forecasting A m a z o n T e x t r a c t A m a z o n p e r s o n a l i z e Recommendations A m a z o n E C 2 P 3 & P 3 D N A m a z o n E C 2 C 5 F P G A s A W S G r e e n g r a s s A m a z o n E l a s t i c I n f e r e n c e A m a z o n I n f e r e n t i a
91. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark There’s Never Been A Better Time To Build New Businesses aws.com/ml
92. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. © 2018, Amazon Web Services, Inc. or its Affiliates. All rights reserved. Amazon Confidential and Trademark Thank You! Adrian Hornsby Sr. Technical Evangelist | Amazon Web Services @adhorn