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Building AI Agents for Finance. Build and deploy robust financial agentic systems with advanced reasoning, architectures, and Python Hanane Dupouy, Fayssal El Mofatiche

Książka w języku angielskim angielski
Building AI Agents for Finance. Build and deploy robust financial agentic systems with advanced reasoning, architectures, and Python Hanane Dupouy, Fayssal El Mofatiche - okladka książki

Building AI Agents for Finance. Build and deploy robust financial agentic systems with advanced reasoning, architectures, and Python Hanane Dupouy, Fayssal El Mofatiche - okladka książki

Building AI Agents for Finance. Build and deploy robust financial agentic systems with advanced reasoning, architectures, and Python Hanane Dupouy, Fayssal El Mofatiche - audiobook MP3

Building AI Agents for Finance. Build and deploy robust financial agentic systems with advanced reasoning, architectures, and Python Hanane Dupouy, Fayssal El Mofatiche - audiobook CD

Autorzy:
Hanane Dupouy, Fayssal El Mofatiche
Ocena:
6.0/6  Opinie: 1
Stron:
756
Dostępne formaty:
     PDF
     ePub

Ebook
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AI agents are rapidly changing how financial systems analyze information, make decisions, and automate complex workflows. While many resources explain agentic AI concepts, few show how to design and deploy AI agents that work reliably in finance. This book fills that gap.
You will start by learning what AI agents are, how they differ from non-agentic systems, and when agentic architectures are appropriate. You’ll use Python with Claude and OpenAI models across hands-on labs covering design patterns, memory, agentic RAG, framework selection, reasoning paradigms such as ReAct, reflection, self-consistency, and Language Agent Tree Search, and multi-agent collaboration. You’ll then take a deep dive into financial use cases, including fundamental analysis, deep research, trading, insurance, and compliance, using technologies such as LangGraph, Claude Skills, the OpenAI Agents SDK, and LlamaIndex.
You will learn to evaluate agent behavior, calibrate LLM judges, detect drift, and produce model risk reports. Finally, you will focus on operationalizing AI agents responsibly, covering the agent harness and execution loop, observability and tracing, deployment and versioning, guardrails, and governance with human oversight.

By the end, you’ll be able to design, evaluate, and deploy financial AI agents that deliver real business value.


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O autorach książki

Hanane Dupouy is Director and Algorithmic Trader at Bernstein, where she designs and implements equity trading strategies to execute client orders with precision and efficiency. She holds an engineering degree and a specialized masters in finance from leading French business schools, and began her career managing a team of data scientists and business intelligence professionals at a major French bank. Over the past six years, Hanane has transitioned fully into algorithmic trading, leveraging machine learning, generative AI, AI agents, and retrieval augmented generation RAG to build and optimize trading systems that adapt to rapidly changing market conditions. Outside of trading, Hanane shares her expertise through her blog,machinelearning basics, where she provides in depth tutorials on technical indicators, AI driven finance, and algorithmic trading best practices. She is also a frequent speaker at industry events, including the CFA UK Technology & Innovation Skills webinars, discussing the practical application of AI frameworks in financial contexts. A CFA charterholder, Hanane combines technical rigor with strategic vision to bridge the gap between cutting edge technology and practical business solutions.
Fayssal El Mofatiche is the Founder and CEO of Flowistic and Finteda, where he focuses on building intelligent, agent-driven systems for financial decision-making and automation. With a strong foundation in finance, technology, and entrepreneurship, he has worked extensively on designing scalable AI architectures that operate reliably in real-world financial contexts.. Fayssal combines hands-on engineering experience with a deep understanding of financial markets, risk, and product strategy. As a CAIA charterholder, he brings a disciplined investment and risk-aware mindset to AI system design. Through his work as a founder, practitioner, and educator, Fayssal helps bridge the gap between advanced AI research and practical, production-ready applications in finance.

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