QuSandbox+NVIDIA Rapids
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The document discusses the capabilities of qusandbox, an end-to-end workflow system for machine learning and AI applications that allows users to create and deploy data science workflows without installing software. It features support for various platforms and programming languages, enabling remote running of applications, concurrent experiments, and model management. Additionally, it highlights the importance of reproducibility in data science, offering tools and case studies for effective implementation in both enterprise and academic settings.
QuSandbox+NVIDIA Rapids
- 1. Scaling AI/ML applications with NVIDIA Rapids with the QuSandbox 2019 Copyright QuantUniversity LLC. Presented By: Sri Krishnamurthy, CFA, CAP [email protected] www.analyticscertificate.com
- 2. 2 About us: • Data Science, Quant Finance and Machine Learning Startup • Expertise in MATLAB, Python,R • Programs ▫ Analytics Certificate Program ▫ Fintech programs • Platform
- 3. • Founder of QuantUniversity LLC. and www.analyticscertificate.com • Advisory and Consultancy for Financial Analytics • Prior Experience at MathWorks, Citigroup and Endeca and 25+ financial services and energy customers. • Regular Columnist for the Wilmott Magazine • Author of forthcoming book “Financial Modeling: A case study approach” published by Wiley • Charted Financial Analyst and Certified Analytics Professional • Teaches Analytics, ML & AI in the Babson College MBA program and at Northeastern University, Boston Sri Krishnamurthy Founder and CEO 3
- 4. 4 The Virtuous Circle of Machine Learning and AI 4 Smart Algorithms Hardware Data
- 5. 5 The rise of Big Data and Data Science 5 Image Source: http://www.ibmbigdatahub.com/sites/default/files/infographic_file/4-Vs-of-big-data.jpg
- 6. 6 Smart Algorithms 6 Distributing Computing Frameworks Deep Learning Frameworks 1. Our labeled datasets were thousands of times too small. 2. Our computers were millions of times too slow. 3. We initialized the weights in a stupid way. 4. We used the wrong type of non-linearity. - Geoff Hinton “Capital One was able to determine fraudulent credit card applications in 100 milliseconds”* * http://go.databricks.com/hubfs/pdfs/Databricks-for-FinTech-170306.pdf
- 7. 7 Hardware Speed up calculations with 1000s of processors Scale computations with infinite compute power
- 8. 8 The Scaling problem in Machine Learning Source: https://arxiv.org/pdf/1802.09941.pdf
- 9. 9 The Scaling problem in Machine Learning Source: https://arxiv.org/pdf/1802.09941.pdf
- 10. 10 The Scaling problem in Machine Learning Source: https://arxiv.org/pdf/1802.09941.pdf
- 11. 11 The Scaling problem in Machine Learning Source: https://www.podc.org/data/podc2018/podc2018- tutorial-alistarh.pdf
- 12. 12 Introducing NVIDIA’s Rapids.ai Screenshots from https://rapids.ai
- 17. 17 • cuDF, a pandas-like dataframe manipulation library • cuML, a collection of machine learning libraries that will provide GPU versions of algorithms available in scikit-learn • cuGraph, a network-X like API that seamlessly integrate into the RAPIDS data science platform NVIDIA Cuda libraries
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- 20. 20 • QUSandbox, is an end-to-end workflow based system to enable creation and deployment of data science workflows within the enterprise for primarily ML and AI applications. • QUSandbox enables trying out enterprise(For example MATLAB, NVIDIA Rapids) and open source products(Tensorflow, R etc.) on the cloud without having to install any software on your devices. The only thing you need is a working browser • QUSandbox supports AWS and Google Cloud platform and incorporates model and data provenance throughout the life cycle of model development. • QUSandbox can also be hosted on-prem to leverage custom hardware and software integrations. Executive Summary
- 21. 21 Prototype Standardize workflow Productionize and share Model Management with QuSandbox
- 22. 22 What’s needed for reproducibility Code Data Environment Process
- 23. 23 QUSandbox solution suite for ML/AI applications Model Analytics Studio QUSandbox Research hub
- 24. 24 ResearchHub
- 26. 26 QuSandbox
- 27. 27 Try applications, datasets, examples with the QuSandbox
- 28. 28 Enterprise product trials can be done with QuSandbox
- 29. 29 Quant/Enterprise use cases • Create an environment that can support multiple platforms and programming languages • Enable remote running of applications • Ability to try out a Github submission/ someone else’s code • Facilitate creation of Docker images to create replicable containers • Create prototyping environments for Data Science/Quant teams • Enable Data scientists/Quants to deploy their solutions • Enable running multiple tasks and jobs • Enable concurrent running of multiple experiments • Integrate seamlessly with the cloud to scale up computations Use cases
- 30. 30 Academic use cases • Enable creation of course material and exercises that could be shared • Enable students and workshop participants to focus on the data science experiments rather than environment setting Use cases
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- 32. 32 Density-based spatial clustering of applications with noise (DBSCAN) 'It is a density-based clustering non- parametric algorithm: given a set of points in some space, it groups together points that are closely packed together (points with many nearby neighbors), marking as outliers points that lie alone in low-density regions (whose nearest neighbors are too far away)’1 1 https://en.wikipedia.org/wiki/DBSCAN DBScan
- 33. 33 Mortgage case study See https://rapids.ai for details
- 34. 34 Request a demo at www.QUSandbox.com
- 35. 35 4-week online course in AI & ML in Finance July 6-31st2019 - Online 1-day class in AI &ML in Finance July 16th 2019 – Online & New York 1.5 hour Master Class in AI & ML in Finance June 6th 2019 – Boston, MA Upcoming classes https://cfa-sf.org/events/EventDetails.aspx?id=1235042 https://www.cfany.org/events/ https://www.cfaboston.org/store/events/registration.aspx?event=060719
- 36. Sri Krishnamurthy, CFA, CAP Founder and Chief Data Scientist QuantUniversity LLC. srikrishnamurthy www.QuantUniversity.com www.analyticscertificate.com www.qusandbox.com Information, data and drawings embodied in this presentation are strictly a property of QuantUniversity LLC. and shall not be distributed or used in any other publication without the prior written consent of QuantUniversity LLC. 36