ML4T covers end-to-end machine learning for trading workflow, from the idea and feature engineering to model optimization, strategy design, and backtesting. Highlights include:
adapting generative adversarial networks (GAN) to create synthetic time series
designing autoencoders to learn risk factors conditional on stock characteristics
applying convolutional neural networks to time series converted to image format
Stefan is the founder and CEO of Applied AI. He advises Fortune 500 companies, investment firms, and startups
across industries on data & AI strategy, building data science teams, and developing end-to-end machine
Before his current venture, he was a partner and managing director at an international investment firm, where he built the predictive analytics and investment research practice. He was also a senior executive at a global fintech company with operations in 15 markets, advised Central Banks in emerging markets, and consulted for the World Bank.
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