Machine Learning For Financial Risk Management With Python by Abdullah Karasan (Author)
- Publisher: COMPUTER SCIENCE
- Availability: In Stock
- SKU: 48552
- Number of Pages: 331
Rs.740.00
Rs.1,050.00
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"Machine Learning For Financial Risk Management With Python" by Abdullah Karasan is a comprehensive guide that explores the intersection of machine learning and finance. This book delves into how machine learning algorithms and Python programming can be harnessed to manage and mitigate financial risks effectively. The author, Abdullah Karasan, brings a wealth of knowledge and practical insights, making this book a valuable resource for financial analysts, data scientists, and anyone interested in applying machine learning techniques to the financial sector. Through a blend of theoretical foundations and practical examples, Karasan illustrates how to develop robust risk management models that can adapt to the dynamic nature of financial markets.
The book covers a wide range of topics, including data preprocessing, feature selection, model evaluation, and the implementation of various machine learning algorithms such as regression analysis, decision trees, and neural networks. It emphasizes the importance of Python as a versatile tool for financial analysis and demonstrates its application through detailed coding examples. Readers will gain a deep understanding of how to leverage machine learning to predict and manage potential risks, enhancing their ability to make informed decisions in the financial industry. This book not only serves as a practical guide but also as an essential reference for mastering the complexities of financial risk management using advanced machine learning techniques.
keypoints:
- Comprehensive guide to using machine learning for financial risk management.
- Detailed coverage of Python programming applications in finance.
- Practical examples and coding demonstrations.
- In-depth exploration of various machine learning algorithms.
- Emphasis on data preprocessing, feature selection, and model evaluation.
- Suitable for financial analysts, data scientists, and finance professionals.
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Writer ✤ Abdullah Karasan (Author)