Machine Learning in Finance: Moving forward!

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© 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

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© 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

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© 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.

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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/

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© 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.

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© 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

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© 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

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© 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.

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© 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.

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© 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/

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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 price of this book is €45 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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© 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

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© 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/

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© 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

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© 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

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© 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

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© 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

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© 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

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© 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

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