Application of AI in Credit Scoring Modeling

Main
Application of AI in Credit Scoring...

Application of AI in Credit Scoring Modeling

Bohdan Popovych

0 / 0

Avez-vous aimé ce livre?

Quelle est la qualité du fichier téléchargé?

Veuillez télécharger le livre pour apprécier sa qualité

Quelle est la qualité des fichiers téléchargés?

Année:

2022

Editeur::

Springer Gabler

Langue:

english

Pages:

92

ISBN 10:

3658401796

ISBN 13:

9783658401795

Collection:

BestMasters

Fichier:

PDF, 1.27 MB

IPFS:

,

english, 2022

Lire en ligne

La conversion en est effectuée

La conversion en a échoué

Cela peut vous intéresser

Jayagopal B. — Applying Data Mining Techniques to Credit Scoring

Raymond A. Anderson — Credit Intelligence & Modelling: Many Paths through the Forest of Credit Rating and Scoring

Raymond Anderson — The Credit Scoring Toolkit: Theory and Practice for Retail Credit Risk Management and Decision Automation

Steven Finlay — Credit Scoring, Response Modelling and Insurance Rating: A Practical Guide to Forecasting Consumer Behaviour

Thomas, David Edelman, Jonathan Crook — Credit Scoring & Its Applications (Monographs on Mathematical Modeling and Computation)

Iain L. J. Brown, PhD — Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Application

Iain L. J. Brown, PhD — Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Application

Galit Shmueli, Peter C. Bruce, Inbal Yahav, Nitin R. Patel, Kenneth C. Lichtendahl, Jr. — Data Mining for Business Analytics

James D. Miller, Rui Miguel Forte — Mastering Predictive Analytics with R - Second Edition

Aydede, Yigit; — Machine Learning Toolbox for Social Scientists

Pratap Dangeti — Statistics for Machine Learning: Techniques for exploring supervised, unsupervised, and reinforcement learning models with Python and R

James D. Miller, Rui Miguel Forte — Mastering Predictive Analytics with R - Second Edition

Miller, James D. & Forte, Rui Miguel — Mastering Predictive Analytics with R

Burger, Scott V — Introduction to machine learning with R: rigorous mathematical analysis

Hearty, John;Julian, David;Raschka, Sebastian — Python deeper insights into machine learning: leverage benefits of machine learning techniques using Python: a course in three modules

Yigit Aydede — Machine Learning Toolbox for Social Scientists

Kenneth C. Lichtendahl, Jr. — Data Mining for Business Analytics: Concepts, Techniques, and Applications in R

Scott V. Burger — Introduction to Machine Learning with R. Rigorous Mathematical Analysis

N.D. Lewis — Machine Learning made easy with R

Dr. Iain Brown — Developing Credit Risk Models Using SAS Enterprise Miner and SAS/STAT: Theory and Applications

Forte, Rui Miguel;Miller, James D — Mastering Predictive Analytics with R

Hearty, John;Julian, David;Raschka, Sebastian — Python deeper insights into machine learning: leverage benefits of machine learning techniques using Python: a course in three modules

John Hearty — Python: Deeper Insights Into Machine Learning

Tony Fischetti, Eric Mayor, & Rui Miguel Forte — R: Predictive Analysis

Dangeti, Pratap — Statistics for machine learning: build supervised, unsupervised, and reinforcement learning models using both Python and R

Pratap Dangeti — Statistics for Machine Learning

Gnana Lakshmi T C, Madeleine Shang — Hands-on Supervised Learning with Python: Learn How to Solve Machine Learning Problems with Supervised Learning Algorithms Using Python

Sebastian Raschka & David Julian & John Hearty [Raschka, Sebastian] — Python: Deeper Insights into Machine Learning

Mots Clefs