Validation and Machine Learning - Some thoughts on Deep Neural Networks
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qusummerschool.splashthat.com Lecture 1: Dr.Jorg Kientz In this talk we outline the use of Machine Learning algorithms and their potential application. We focus on Deep Neural Networks. The aim is to outline different network architectures. Then, we wish to find a way of choosing the architecture that best fits from a model validation perspective. This approach is illustrated with examples. Lecture 2: Ben Steiner In this talk we will discuss the challenges of Deep learning and focus on the key aspects of Model Risk Management for Deep Learning and Alpha Strategies
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Validation and Machine Learning - Some thoughts on Deep Neural Networks
- 1. Qu Speaker Series Validation and Machine Learning - Some thoughts on Deep Neural Networks 2020 Copyright QuantUniversity LLC. Hosted By: Sri Krishnamurthy, CFA, CAP sri@quantuniversity.com www.qu.academy 09/09/2020 Online https://quspeakerseries9.splashthat.com/
- 2. 2 QuantUniversity • Boston-based Data Science, Quant Finance and Machine Learning training and consulting advisory • Trained more than 1000 students in Quantitative methods, Data Science and Big Data Technologies using MATLAB, Python and R • Building a platform for AI and Machine Learning Exploration and Experimentation
- 3. For registration information, go to https://QuSummerSchool.splashthat.com 3
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- 6. 6 Validation and Machine Learning - Some thoughts on Deep Neural Networks
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- 9. 9 Demos, slides and video available on QuAcademy Go to www.qu.academy 9
- 10. 10 Instructions for the Lab: 1. Go to https://academy.qusandbox.com/#/register and register using the code: "QUSUMMERSCHOOL" 2. Go to: https://academy.qusandbox.com/#/market/5f3c39ff99aa4a24691da5f3 3. Click on "Run on QuSandbox" to access the lab
- 11. Thank you! Sri Krishnamurthy, CFA, CAP Founder and CEO QuantUniversity LLC. srikrishnamurthy www.QuantUniversity.com Contact 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. 11