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Machine Learning and Data Science Blueprints for Finance - From Building Trading Strategies to Robo-Advisors Using Python (Paperback) Loot Price: R1,324
Discovery Miles 13 240
Machine Learning and Data Science Blueprints for Finance - From Building Trading Strategies to Robo-Advisors Using Python...

Machine Learning and Data Science Blueprints for Finance - From Building Trading Strategies to Robo-Advisors Using Python (Paperback)

Hariom Tatsat, Sahil Puri, Brad Lookabaugh

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Loot Price R1,324 Discovery Miles 13 240 | Repayment Terms: R124 pm x 12*

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Over the next few decades, machine learning and data science will transform the finance industry. With this practical book, analysts, traders, researchers, and developers will learn how to build machine learning algorithms crucial to the industry. You'll examine ML concepts and over 20 case studies in supervised, unsupervised, and reinforcement learning, along with natural language processing (NLP). Ideal for professionals working at hedge funds, investment and retail banks, and fintech firms, this book also delves deep into portfolio management, algorithmic trading, derivative pricing, fraud detection, asset price prediction, sentiment analysis, and chatbot development. You'll explore real-life problems faced by practitioners and learn scientifically sound solutions supported by code and examples. This book covers: Supervised learning regression-based models for trading strategies, derivative pricing, and portfolio management Supervised learning classification-based models for credit default risk prediction, fraud detection, and trading strategies Dimensionality reduction techniques with case studies in portfolio management, trading strategy, and yield curve construction Algorithms and clustering techniques for finding similar objects, with case studies in trading strategies and portfolio management Reinforcement learning models and techniques used for building trading strategies, derivatives hedging, and portfolio management NLP techniques using Python libraries such as NLTK and scikit-learn for transforming text into meaningful representations

General

Imprint: O'Reilly Media
Country of origin: United States
Release date: November 2020
Authors: Hariom Tatsat • Sahil Puri • Brad Lookabaugh
Dimensions: 233 x 178 x 24mm (L x W x T)
Format: Paperback
Pages: 428
ISBN-13: 978-1-4920-7305-5
Categories: Books
LSN: 1-4920-7305-9
Barcode: 9781492073055

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