Stefan Jansen is the author of the widely read ‘Machine Learning For Algorithmic Trading’. He is the founder and Lead Data Scientist at Applied AI. He advises Fortune 500 companies, investment firms and startups across industries on data & AI strategy and developing machine learning solutions. Before his current venture, he was a partner at Infusive, an international investment firm, where he built the predictive analytics and investment research practice. He also was a senior executive at Rev Worldwide, a global fintech company focused on payments. Earlier, he advised Central Banks in emerging markets, and consulted for the World Bank. In this podcast we discuss:
What benefits does machine learning bring that other techniques don’t have
The challenge of using machine learning in finance
What is ChatGPT and the underlying tech of LLMs?
Understanding neural networks
The 2017 Google breakthrough that led to ChatGPT
How AI can understand sentences
Uses for ChatGPT and LLMs
Common machine learning techniques
How to use decision trees, random forests and gradient boosting
Using neural networks in finance
You can find Stefan’s research here and his Github here.
(The commentary contained in the above article does not constitute an offer or a solicitation, or a recommendation to implement or liquidate an investment or to carry out any other transaction. It should not be used as a basis for any investment decision or other decision. Any investment decision should be based on appropriate professional advice specific to your needs.)
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