文件名称:
Packt.Practical.Machine.Learning.2016
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文件大小: 16mb
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上传时间: 2017-08-09
详细说明： Foreword Can machines think? This question has fascinated scientists and researchers around the world. In the 1950s, Alan Turing shifted the paradigm from “Can machines think?” to “Can machines do what humans (as thinking entities) can do?”. Since then, the fiel d of Machine learning/Artificial Intelligence continues to be an exciting topic and considerable progress has been made. The advances in various computing technologies, the pervasive use of computing devices, and resultant Information/Data glut has shifted the focus of Machine learning from an exciting esoteric field to prime time. Today, organizations around the world have understood the value of Machine learning in the crucial role of knowledge discovery from data, and have started to invest in these capabilities. Most developers around the world have heard of Machine learning; the “learning” seems daunting since this field needs a multidisciplinary thinking—Big Data, Statistics, Mathematics, and Computer Science. Sunila has stepped in to fill this void. She takes a fresh approach to mastering Machine learning, addressing the computing side of the equation-handling scale, complexity of data sets, and rapid response times. Practical Machine Learning is aimed at being a guidebook for both established and aspiring data scientists/analysts. She presents, herewith, an enriching journey for the readers to understand the fundamentals of Machine learning, and manages to handhold them at every step leading to practical implementation path. She progressively uncovers three key learning blocks. The foundation block focuses on conceptual clarity with a detailed review of the theoretical nuances of the disciple. This is followed by the next stage of connecting these concepts to the real-world problems and establishing an ability to rationalize an optimal application. Finally, exploring the implementation aspects of latest and best tools in the market to demonstrate the value to the business users. ...展开收缩
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