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Hands-On Machine Learning for Algorithmic Trading

Design and implement investment strategies based on smart algorithms that learn from data using Python
BuchKartoniert, Paperback
684 Seiten
Englisch
Packt Publishingerschienen am31.12.2018
With the help of this book, you'll build smart algorithmic models using machine learning algorithms covering tasks such as time series forecasting, backtesting, trade predictions, and more using easy-to-follow examples. By the end, you'll be able to adopt algorithmic trading in your own business and implement intelligent investigative strategies.mehr

Produkt

KlappentextWith the help of this book, you'll build smart algorithmic models using machine learning algorithms covering tasks such as time series forecasting, backtesting, trade predictions, and more using easy-to-follow examples. By the end, you'll be able to adopt algorithmic trading in your own business and implement intelligent investigative strategies.
Details
ISBN/GTIN978-1-78934-641-1
ProduktartBuch
EinbandartKartoniert, Paperback
Erscheinungsjahr2018
Erscheinungsdatum31.12.2018
Seiten684 Seiten
SpracheEnglisch
MasseBreite 191 mm, Höhe 235 mm, Dicke 37 mm
Gewicht1255 g
Artikel-Nr.49991855

Inhalt/Kritik

Inhaltsverzeichnis
Table of ContentsMachine Learning for TradingMarket and Fundamental DataAlternative Data for FinanceAlpha Factor ResearchStrategy EvaluationThe Machine Learning ProcessLinear ModelsTime Series ModelsBayesian Machine LearningDecision Trees and Random ForestsGradient Boosting MachinesUnsupervised LearningWorking with Text DataTopic ModelingWord EmbeddingsNext Stepsmehr

Autor

Stefan is the founder and CEO of Applied AI. He advises Fortune 500 companies, investment firms, and startups across industries on data & AI strategy, building data science teams, and developing end-to-end machine learning solutions for a broad range of business problems. Before his current venture, he was a partner and managing director at an international investment firm, where he built the predictive analytics and investment research practice. He was also a senior executive at a global fintech company with operations in 15 markets, advised Central Banks in emerging markets, and consulted for the World Bank. He holds Master's degrees in Computer Science from Georgia Tech and in Economics from Harvard and Free University Berlin, and a CFA Charter. He has worked in six languages across Europe, Asia, and the Americas and taught data science at Datacamp and General Assembly.