Book (Practical) Information science Practical! NumPy Data-Processing Primer, 2nd edition High-speed processing techniques useful in machine learning and data science / Takuma Yoshida / So Ohara

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Information Science
AI & TECHNOLOGY / Long-awaited 2nd Edition Detailed explanation of high-speed data processing techniques using Numpy, which is useful in machine learning and data science fields. In this book, we picked up NumPy, which is often used in machine learning and data science fields. Starting with the basics of Numpy, we explained practical high-speed data processing techniques that can be used in the field. Especially, we focused on processing arrays. In the last chapter, we explained practical data-processing techniques in machine learning. [Changes in the 2nd Edition] ・ Support for Python 311 ・ Updates to various libraries NumPy is a library that is rich in high-level mathematical functions for processing multidimensional arrays (matrices and vectors) that are often handled in machine learning and data science fields. It starts with the basics of Numpy, and explains practical high-speed data processing techniques that can be used in the field. Especially, we focused on processing arrays. In the last chapter, we explained practical data-processing techniques in machine learning. [What is NumPy?] NumPy is a library that is rich in high-level mathematical functions for processing multidimensional arrays (matrices and vectors) that are often handled in machine learning and data science fields. Even if it is slow by itself, it can be as fast as C-language, so it is an indispensable library for processing in machine learning and data science. [Audience] ・ Machine Learning Engineers ・ Data Scientists [Contents] Chapter1 NumPy Basics Chapter2 NumPy Know functions for manipulating arrays Using Chapter3 NumPy Mathematical Functions Implementing Machine Learning in Chapter4 NumPy [Author profile] Takuma Yoshida, Representative Director and President of Spot Co., Ltd., a provider of data science-related services. Using Chapter3 NumPy's Mathematical Functions. Implementing Machine Learning in Chapter4 NumPy Takuma, Chief Editor of 』, 『 DeepAge, Web Media. So Ohara