Parametri
- 400pagine
- 14 ore di lettura
Maggiori informazioni sul libro
Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.
Acquisto del libro
Advances in Financial Machine Learning, Marcos López de Prado
- Lingua
- Pubblicato
- 2018
- Rilegatura
- (Copertina rigida)
Metodi di pagamento
Ancora nessuna valutazione.
- Titolo
- Advances in Financial Machine Learning
- Lingua
- Inglese
- Autori
- Marcos López de Prado
- Editore
- WILEY
- Pubblicato
- 2018
- Formato
- Copertina rigida
- Pagine
- 400
- ISBN10
- 1119482089
- ISBN13
- 9781119482086
- Serie
- Categoria
- Tag
- Commercio, USA, Tecnologia, Finanza, Intelligenza artificiale, Investimenti, Elaborazione dei dati, Apprendimento Automatico
- Descrizione
- Machine learning (ML) is changing virtually every aspect of our lives. Today ML algorithms accomplish tasks that until recently only expert humans could perform. As it relates to finance, this is the most exciting time to adopt a disruptive technology that will transform how everyone invests for generations. Readers will learn how to structure Big data in a way that is amenable to ML algorithms; how to conduct research with ML algorithms on that data; how to use supercomputing methods; how to backtest your discoveries while avoiding false positives. The book addresses real-life problems faced by practitioners on a daily basis, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their particular setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.