Cargando…

Hands-on machine learning for algorithmic trading bots with Python.

Introducing the study of machine learning and algorithmic trading for financial practitioner About This Video Building high-frequency trading robots Applying feature engineering on stock market data Diving deeper into the pros and cons of various financial data structures Building & evaluating m...

Descripción completa

Detalles Bibliográficos
Clasificación:Libro Electrónico
Formato: Electrónico Video
Idioma:Inglés
Publicado: [Place of publication not identified] : Packt Publishing, [2019]
Edición:[First edition].
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

LEADER 00000cgm a22000007i 4500
001 OR_on1310490401
003 OCoLC
005 20231017213018.0
006 m o c
007 vz czazuu
007 cr cnannnuuuuu
008 220412s2019 xx 291 o vleng d
040 |a ORMDA  |b eng  |e rda  |e pn  |c ORMDA  |d ORMDA  |d OCLCO  |d OCLCF  |d OCLCO 
024 8 |a 9781789951165 
029 1 |a AU@  |b 000071968874 
035 |a (OCoLC)1310490401 
037 |a 9781789951165  |b O'Reilly Media 
050 4 |a Q325.5 
082 0 4 |a 006.3/1  |2 23 
049 |a UAMI 
245 0 0 |a Hands-on machine learning for algorithmic trading bots with Python. 
246 3 0 |a Machine learning for algorithmic trading bots with Python 
250 |a [First edition]. 
264 1 |a [Place of publication not identified] :  |b Packt Publishing,  |c [2019] 
300 |a 1 online resource (1 video file (4 hr., 51 min.)) :  |b sound, color. 
306 |a 045100 
336 |a two-dimensional moving image  |b tdi  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
344 |a digital  |2 rdatr 
347 |a video file  |2 rdaft 
380 |a Instructional films  |2 lcgft 
511 0 |a Mustafa Qamar-ud-Din, presenter. 
520 |a Introducing the study of machine learning and algorithmic trading for financial practitioner About This Video Building high-frequency trading robots Applying feature engineering on stock market data Diving deeper into the pros and cons of various financial data structures Building & evaluating many machine learning models Implementing backtesting econometrics for trading strategies evaluation Hacking Ensemble Learning Algorithms in Machine Learning Featuring a premiere on Ensemble Learning with Bagging & Boosting Experience-based tutorials and hands-on financial challenges In Detail Have you ever wondered how the Stock Market, Forex, Cryptocurrency and Online Trading works? Have you ever wanted to become a rich trader having your computers work and make money for you while you're away for a trip in the Maldives? Ever wanted to land a decent job in a brokerage, bank, or any other prestigious financial institution?We have compiled this course for you in order to seize your moment and land your dream job in financial sector. This course covers the advances in the techniques developed for algorithmic trading and financial analysis based on the recent breakthroughs in machine learning. We leverage the classic techniques widely used and applied by financial data scientists to equip you with the necessary concepts and modern tools to reach a common ground with financial professionals and conquer your next interview.By the end of the course, you will gain a solid understanding of financial terminology and methodology and a hands-on experience in designing and building financial machine learning models. You will be able to evaluate and validate different algorithmic trading strategies. We have a dedicated section to backtesting which is the holy grail of algorithmic trading and is an essential key to successful deployment of reliable algorithms. Audience This course is compiled for data science beginners and professionals who want to shift their career to financial sector. This course assumes a basic knowledge of Python programming such as conditional and looping statements. The course is self contained in terms of the concepts, theories, and technologies it requires to build trading bots. 
588 0 |a Online resource; title from title details screen (O'Reilly, viewed April 12, 2022). 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
650 0 |a Machine learning. 
650 0 |a Python (Computer program language) 
650 2 |a Machine Learning 
650 6 |a Apprentissage automatique. 
650 6 |a Python (Langage de programmation) 
650 7 |a Machine learning  |2 fast 
650 7 |a Python (Computer program language)  |2 fast 
655 2 |a Webcast 
655 7 |a Instructional films  |2 fast 
655 7 |a Internet videos  |2 fast 
655 7 |a Nonfiction films  |2 fast 
655 7 |a Instructional films.  |2 lcgft 
655 7 |a Nonfiction films.  |2 lcgft 
655 7 |a Internet videos.  |2 lcgft 
655 7 |a Films de formation.  |2 rvmgf 
655 7 |a Films autres que de fiction.  |2 rvmgf 
655 7 |a Vidéos sur Internet.  |2 rvmgf 
700 1 |a Qamar-ud-Din, Mustafa,  |e presenter. 
710 2 |a Packt Publishing,  |e publisher. 
856 4 0 |u https://learning.oreilly.com/videos/~/9781789951165/?ar  |z Texto completo (Requiere registro previo con correo institucional) 
994 |a 92  |b IZTAP