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Artificial Intelligence in Finance: A Python-Based Guide
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Artificial Intelligence in Finance: A Python-Based Guide
With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading.
Artificial Intelligence in Finance: A Python-Based Guide
Artigo n.º: 41223672

Artificial Intelligence in Finance: A Python-Based Guide

88% of respondents would recommend this to a friend

Artigo n.º: 41223672

MZN 4283

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With this practical book, you'll learn how to use AI and machine learning to discover statistical inefficiencies in financial markets and exploit them through algorithmic trading.
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O que se Destaca

Comprehensive Coverage
This guide provides an extensive exploration of AI applications in finance, catering to both beginners and advanced practitioners, ensuring a deep understanding of key concepts and methodologies.
Python Integration
Leveraging Python's robust ecosystem, this book offers practical coding examples and hands-on projects, allowing readers to implement AI solutions directly, bridging the gap between theory and real-world application.
Industry-Relevant Insights
With a focus on real-world challenges, the text addresses pressing finance issues, delivering insights that enhance decision-making and forecasting accuracy in diverse financial scenarios.

Detalhes do produto

Discover the power of AI in finance with this comprehensive Python-based guide. Learn the latest techniques and strategies for success. Shop now at Ubuy Mozambique.
  • Provides practical insights and examples of AI-based algorithmic trading in the financial sector
  • Based on the author's practical experience in developing, testing, and implementing AI-powered trading strategies
  • Presents Python-based code examples and applications in financial trading
  • Focuses on empowering readers to explore AI in financial trading using provided code examples
  • Complementary resources available for deeper understanding of Python for finance and algorithmic trading strategies
  • The book’s approach to deriving features assumes patterns in financial time series data that persist over time
Publisher O'Reilly Media
Publication date November 17, 2020
Edition 1st
Language English
Print length 475 pages
ISBN-10 1492055433
ISBN-13 978-1492055433
Item Weight 2.31 pounds (1.05 kg)
Dimensions 7 x 0.96 x 9.19 inches (17.8 x 2.4 x 23.3 cm)

Quem Deverá Comprar?

Suitable For
  • Finance Professionals

    Finance experts looking to leverage AI for predictive analytics and decision-making will find this guide invaluable.

  • Data Scientists

    Data scientists interested in applying Python for financial modeling will benefit from practical examples and coding insights.

  • Students and Learners

    Students in finance or data science can use this guide as a comprehensive introduction to AI applications in finance.

Not Suitable For
  • Beginners in Finance

    Complete novices with no background in finance may find the content too advanced and overwhelming to understand.

DESCRIÇÃO DO PRODUTO

Artificial Intelligence in Finance: A Python-Based Guide

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Perguntas e respostas do cliente

  • Pergunta: What is 'Artificial Intelligence in Finance: A Python-Based Guide' about?

    Resposta: 'Artificial Intelligence in Finance: A Python-Based Guide' explores the application of AI technologies in financial markets. It provides a practical understanding of how Python can be utilized to implement AI algorithms and data analysis techniques. This guide is beneficial for finance professionals who want to enhance their analytical skills with programming and deepen their understanding of AI applications in risk management, fraud detection, and algorithmic trading.
  • Pergunta: Who is the target audience for this book?

    Resposta: This book primarily targets finance professionals, data analysts, and students pursuing careers in finance and technology. It is also useful for software developers seeking to understand the financial applications of AI. The content caters to readers with varying levels of expertise in programming and finance, making it accessible for both beginners and experienced practitioners in the field.
  • Pergunta: What skills can I expect to gain from this book?

    Resposta: Readers can expect to gain a strong foundation in utilizing Python for financial modeling and data analysis. The book equips you with practical skills, including how to implement machine learning algorithms, analyze financial datasets, and develop predictive models. These skills are essential for enhancing decision-making processes and optimizing investment strategies in the finance sector.
  • Pergunta: Are there hands-on coding examples included in the book?

    Resposta: Yes, the guide includes numerous hands-on coding examples that readers can follow along with. This practical approach allows you to apply theoretical concepts directly to real-world financial problems. By working through the provided examples, you will gain the confidence to create your own AI-driven financial models and algorithms, enhancing your technical proficiency.
  • Pergunta: What programming knowledge is required to understand the book?

    Resposta: A basic understanding of Python programming is advisable, as the book assumes familiarity with the language's syntax and structure. However, the author provides clear explanations and code snippets for readers who may be less experienced. This makes the book a suitable resource for anyone motivated to learn how to integrate AI into finance, even if they are starting with minimal coding experience.
  • Pergunta: How does artificial intelligence impact the finance sector?

    Resposta: Artificial intelligence significantly transforms the finance sector by enabling data-driven decision-making, improving efficiency, and enhancing the accuracy of financial predictions. AI technologies help in automating tasks such as risk assessment, fraud detection, and customer service through chatbots. By integrating AI tools, companies can streamline their operations and provide personalized services, ultimately leading to better financial outcomes.
  • Pergunta: Can this book help in preparing for finance-related job interviews?

    Resposta: Absolutely! This book serves as an excellent resource for understanding the technical skills required in finance roles, particularly in data analysis and AI applications. By mastering the concepts and coding techniques presented, you’ll be better prepared to discuss relevant projects and problem-solving strategies during job interviews, showcasing your proficiency in merging finance with technology.
  • Pergunta: What are some advanced topics covered in the book?

    Resposta: Some advanced topics include machine learning techniques for credit scoring, algorithmic trading strategies, and neural networks for predictive analytics. The book delves into both supervised and unsupervised learning methods tailored for financial datasets. By tackling these topics, readers can develop a deeper understanding of how to harness powerful AI tools for complex financial analyses and decision-making.
  • Pergunta: How does this book compare to other AI finance guides?

    Resposta: This book stands out by focusing on Python as a versatile tool for financial modeling while providing extensive hands-on exercises. Unlike other guides that might focus solely on theoretical aspects, this book emphasizes practical application, enabling readers to gain immediate skills. Additionally, it integrates real-world financial examples and case studies that make the content relatable and actionable.
  • Pergunta: Where can I buy 'Artificial Intelligence in Finance: A Python-Based Guide 1st Edition' in Mozambique?

    Resposta: You can purchase 'Artificial Intelligence in Finance: A Python-Based Guide 1st Edition' on Ubuy. Ubuy offers a user-friendly platform where you can find this title along with other related products in a seamless shopping experience. Simply visit the Ubuy website and search for the book to explore your options.

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MZN 4283

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Recursos e benefícios

  • Learn to use AI and machine learning in finance
  • Discover statistical inefficiencies in financial markets
  • Exploit inefficiencies through algorithmic trading
  • Understand the impact of AI on finance
  • Apply neural networks and reinforcement learning in finance
  • Replicate presented figures with self-contained Python examples

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