SKU/Artículo: AMZ-1787129624
Practical Data Science Cookbook - Second Edition: Data pre-processing, analysis and visualization using R and Python
Format:
Paperback
Detalles del producto
Disponibilidad:
En stock
En stock
Peso con empaque:
0.74 kg
0.74 kg
Devolución:
Sí
Sí
Condición
Nuevo
Nuevo
Producto de:
Amazon
Amazon
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USA
USA
Sobre este producto
- Over 85 recipes to help you complete real-world data science projects in R and PythonAbout This BookTackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your dataGet beyond the theory and implement real-world projects in data science using R and PythonEasy-to-follow recipes will help you understand and implement the numerical computing conceptsWho This Book Is ForIf you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python.What You Will LearnLearn and understand the installation procedure and environment required for R and Python on various platformsPrepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and PythonBuild a predictive model and an exploratory modelAnalyze the results of your model and create reports on the acquired dataBuild various tree-based methods and Build random forestIn DetailAs increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don't. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract
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