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Large Language Models in Finance. A hands-on guide to applying Large Language Models in trading, banking, risk & financial compliance Miquel Noguer i Alonso

Język publikacji: angielski
Large Language Models in Finance. A hands-on guide to applying Large Language Models in trading, banking, risk & financial compliance Miquel Noguer i Alonso - okladka książki

Large Language Models in Finance. A hands-on guide to applying Large Language Models in trading, banking, risk & financial compliance Miquel Noguer i Alonso - okladka książki

Autor:
Miquel Noguer i Alonso
Serie wydawnicze:
Hands-on
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Large language models are revolutionizing finance from market analysis to compliance automation but applying them in practice can be challenging. LLMs in Finance is a step-by-step guide that demystifies these powerful models and shows you how to implement them in real financial projects. You'll begin with the fundamentals of how LLMs work, including the transformer architecture, prompt engineering, and fine-tuning for financial data. Next, you'll build applications: intelligent agents for trading; tools for banking tasks like credit scoring and fraud detection; and automated solutions for risk management and regulatory compliance. To deploy these solutions, you'll learn how to scale LLM implementations, from choosing the right hardware to adopting effective cloud strategies. You'll also explore advanced methods to improve model performance, including reinforcement learning for fine-tuning. Finally, learn how to address AI bias and ensure your LLM solutions comply with ethical and regulatory requirements. Real-world case studies illustrate how financial organizations are leveraging LLMs in trading systems, customer service chatbots, and more.
By the end of the book, you'll have the expertise to build LLM-powered applications and pick up on trends such as multimodal AI

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O autorze książki

Miquel Noguer i Alonso is a seasoned finance professional with over 30 years of experience in quantitative finance. He co-founded the Artificial Intelligence Finance Institute (AIFI) and has held senior positions at leading financial institutions, including serving as Executive Director at UBS and Chief Investment Officer at Andbank. Miquel is also an active academic, teaching AI and fintech courses at NYU, Columbia University, and other top institutions. He holds an MBA and a degree in business administration from ESADE, as well as a PhD in quantitative finance from UNED. Miquel has published extensively on AI in finance and is a co-editor of the Journal of Machine Learning in Finance

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