Hands-On Data Science and Python Machine Learning (eBook)
420 Seiten
Packt Publishing (Verlag)
978-1-78728-022-9 (ISBN)
Join Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them.
Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis.
This book covers the fundamentals of machine learning with Python in a concise and dynamic manner. It covers data mining and large-scale machine learning using Apache Spark.About This BookTake your first steps in the world of data science by understanding the tools and techniques of data analysisTrain efficient Machine Learning models in Python using the supervised and unsupervised learning methodsLearn how to use Apache Spark for processing Big Data efficientlyWho This Book Is ForIf you are a budding data scientist or a data analyst who wants to analyze and gain actionable insights from data using Python, this book is for you. Programmers with some experience in Python who want to enter the lucrative world of Data Science will also find this book to be very useful, but you don't need to be an expert Python coder or mathematician to get the most from this book.What You Will LearnLearn how to clean your data and ready it for analysisImplement the popular clustering and regression methods in PythonTrain efficient machine learning models using decision trees and random forestsVisualize the results of your analysis using Python's Matplotlib libraryUse Apache Spark's MLlib package to perform machine learning on large datasetsIn DetailJoin Frank Kane, who worked on Amazon and IMDb's machine learning algorithms, as he guides you on your first steps into the world of data science. Hands-On Data Science and Python Machine Learning gives you the tools that you need to understand and explore the core topics in the field, and the confidence and practice to build and analyze your own machine learning models. With the help of interesting and easy-to-follow practical examples, Frank Kane explains potentially complex topics such as Bayesian methods and K-means clustering in a way that anybody can understand them.Based on Frank's successful data science course, Hands-On Data Science and Python Machine Learning empowers you to conduct data analysis and perform efficient machine learning using Python. Let Frank help you unearth the value in your data using the various data mining and data analysis techniques available in Python, and to develop efficient predictive models to predict future results. You will also learn how to perform large-scale machine learning on Big Data using Apache Spark. The book covers preparing your data for analysis, training machine learning models, and visualizing the final data analysis.Style and approachThis comprehensive book is a perfect blend of theory and hands-on code examples in Python which can be used for your reference at any time.
Erscheint lt. Verlag | 31.7.2017 |
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Sprache | englisch |
Themenwelt | Sachbuch/Ratgeber ► Freizeit / Hobby ► Sammeln / Sammlerkataloge |
ISBN-10 | 1-78728-022-5 / 1787280225 |
ISBN-13 | 978-1-78728-022-9 / 9781787280229 |
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