Название: Machine Learning for Finance: Beginner's guide to explore machine learning in banking and finance
Автор: Saurav Singla
Издательство: BPB Publications,
Год: 2021
Формат: True EPUB
Страниц: 391
Размер: 10 Mb
Язык: English

Understand the essentials of Machine Learning and its impact in financial sector
Key Features
Explore the spectrum of machine learning and its usage.
Understand the NLP and Computer Vision and their use cases.
Understand the Neural Network, CNN, RNN and their applications.
Understand the Reinforcement Learning and their applications.
Learn the rising application of Machine Learning in the Finance sector.

Description
The fields of machining adapting, profound learning, and computerized reasoning are quickly extending and are probably going to keep on doing as such for a long time to come. There are many main impetuses for this, as quickly caught in this review. Now and again, the advancement has been emotional, opening new ways to deal with long-standing innovation challenges, for example, progresses in PC vision and picture investigation.
The book demonstrates how to solve some of the most common issues in the financial industry. The book addresses real-life problems faced by practitioners on a daily basis. The book explains how machine learning works on structured data, text, and images. You will cover the exploration of Naïve Bayes, Normal Distribution, Clustering with Gaussian process, advanced neural network, sequence modeling, and reinforcement learning. Later chapters will discuss machine learning use cases in the finance sector and the implications of deep learning. The book ends with traditional machine learning algorithms.
Machine Learning has become very important in the finance industry, which is mostly used for better risk management and risk analysis. Better analysis leads to better decisions which lead to an increase in profit for financial institutions. Machine Learning to empower fintech to make massive profits by optimizing processes, maximizing efficiency, and increasing profitability.