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Mastering Probability and Statistics in Python /

A comprehensive course that teaches you the concepts and methodologies of statistics and probability with data science. About This Video Easy explanations, yet complete and comprehensive course Fundamental, pythonic, and a complete course to master the important concepts used in data science Practic...

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Detalles Bibliográficos
Autor principal: Sciences, AI (Autor)
Autor Corporativo: Safari, an O'Reilly Media Company
Formato: Electrónico Video
Idioma:Inglés
Publicado: Packt Publishing, 2021.
Edición:1st edition.
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

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520 |a A comprehensive course that teaches you the concepts and methodologies of statistics and probability with data science. About This Video Easy explanations, yet complete and comprehensive course Fundamental, pythonic, and a complete course to master the important concepts used in data science Practical with live coding of the implementation of the concepts learned theoretically In Detail In today's ultra-competitive business universe, probability and statistics are the most important fields of study. That is because statistical research presents businesses with the data they need to make informed decisions in every business area, whether it is market research, product development, product launch timing, customer data analysis, sales forecast, or employee performance. But why do you need to master probability and statistics in Python? The answer is that an expert grip on the concepts of statistics and probability with data science will enable you to take your career to the next level. This course is designed carefully to reflect the most in-demand skills that will help you in understanding the concepts and methodology with regard to Python. The course is as follows: Easy to understand Expressive Comprehensive Practical with live coding About establishing links between probability and machine learning By the end of this course, you will be able to relate the concepts and theories in machine learning with probabilistic reasoning and understand the methodology of statistics and probability with data science, using real datasets. 
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