Modern Data Mining with Python A risk-managed approach to developing and deploying explainable and efficient algorithms using ModelOps (English Edition)
-
- Taschenbuch ausgewählt
- eBook
-
Sprache:Englisch
49,99 €
inkl. gesetzl. MwSt.,
Beschreibung
Produktdetails
Einband
Taschenbuch
Erscheinungsdatum
26.02.2024
Verlag
BPB PublicationsSeitenzahl
440
Maße (L/B/H)
23,5/19,1/2,4 cm
Gewicht
816 g
Sprache
Englisch
ISBN
978-93-5551-914-6
Data miner's survival kit for explainable, effective, and efficient algorithms enabling responsible decision-making ¿DESCRIPTION "Modern Data Mining with Python" is a guidebook for responsibly implementing data mining techniques that involve collecting, storing, and analyzing large amounts of structured and unstructured data to extract useful insights and patterns. Enter into the world of data mining and machine learning. Use insights from various data sources, from social media to credit card transactions. Master statistical tools, explore data trends, and patterns. Understand decision trees and artificial neural networks (ANNs). Manage high-dimensional data with dimensionality reduction. Explore binary classification with logistic regression. Spot concealed patterns with unsupervised learning. Analyze text with recurrent neural networks (RNNs) and visuals with convolutional neural networks (CNNs). Ensure model compliance with regulatory standards. After reading this book, readers will be equipped with the skills and knowledge necessary to use Python for data mining and analysis in an industry set-up. They will be able to analyze and implement algorithms on large structured and unstructured datasets. WHAT YOU WILL LEARN ¿ Explore the data mining spectrum ranging from data exploration and statistics. ¿ Gain hands-on experience applying modern algorithms to real-world problems in the financial industry. ¿ Develop an understanding of various risks associated with model usage in regulated industries. ¿ Gain knowledge about best practices and regulatory guidelines to mitigate model usage-related risk in key banking areas. ¿ Develop and deploy risk-mitigated algorithms on self-serve ModelOps platforms. WHO THIS BOOK IS FOR This book is for a wide range of early career professionals and students interested in data mining or data science with a financial services industry focus. Senior industry professionals, and educators, trying to implement data mining algorithms can benefit as well.
Noch keine Bewertungen vorhanden
Verfassen Sie die erste Bewertung zu diesem Artikel
Helfen Sie anderen Kundinnen und Kunden durch Ihre Meinung.
Kurze Frage zu unserer Seite
Vielen Dank für dein Feedback
Wir nutzen dein Feedback, um unsere Produktseiten zu verbessern. Bitte habe Verständnis, dass wir dir keine Rückmeldung geben können. Falls du Kontakt mit uns aufnehmen möchtest, kannst du dich aber gerne an unseren Kund*innenservice wenden.
zum Kundenservice