SKU/Artículo: AMZ-B0CR788HTY

Supervised Learning for Finance: A Comprehensive Guide for the Application of Machine Learning with Python

Format:

Paperback

Kindle

Paperback

Detalles del producto
Disponibilidad:
En stock
Peso con empaque:
0.50 kg
Devolución:
Condición
Nuevo
Producto de:
Amazon
Viaja desde
USA

Sobre este producto
  • Reactive Publishing Dive into predictive analytics with "Supervised Learning for Finance," the essential guide for those poised at the intersection of finance and cutting-edge technology. Building on the foundational algorithms and techniques that captivated readers in its best-selling predecessor, this book elevates your prowess to new heights, offering an unparalleled toolkit for sophisticated financial data analysis and decision-making. Designed specifically for finance professionals who have tasted the power of Python and supervised machine learning, but yearn to master its more advanced applications, this book demystifies complex concepts and empowers you to harness their potential. Whether you're fine-tuning investment strategies, gauging market sentiments, or forecasting economic trends, you'll find in these pages the keys to unlocking the true value of your data. Expert authors guide you through a practical journey, blending theory with real-world applications to not only enhance your technical skills but also your financial acumen. You'll delve into nuanced aspects of regression analysis, classification, and ensemble learning, refined to suit the dynamic world of finance. Explore advanced feature selection, fine-tune predictive models with hyperparameter optimization, and unleash the power of neural networks and decision trees in your analyses. Branch out from the basics and immerse yourself in chapters dedicated to risk management, fraud detection, algorithmic trading, and beyond. Each technique is tailored to tackle the challenges unique to the financial sector, ensuring you can apply what you learn directly to your daily work. With "Supervised Learning for Finance" by your side, you'll: - Advance your machine learning expertise within the context of finance. - Learn to wrangle financial datasets and extract insightful features. - Navigate the subtleties of model validation and error analysis in financial systems. - Discover strategies to overcome overfitting and implement robust cross-validation techniques. - Decode the complexities of time-series forecasting and portfolio optimization. - Stay ahead of the curve with an intro to cutting-edge developments and ethical considerations in AI finance. Perfect for quantitative analysts, investment bankers, risk managers, and any finance professional striving for the leading edge in technology and analysis, this book acts as both a deep dive and a practical reference. The synthesis of Python's powerful capabilities with the precision demands of finance has never been so attainable. Embrace this journey to amplify your career and leave your mark on the future of finance.
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