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 Book * Take your first steps in the world of data science by understanding the tools and techniques of data analysis * Train efficient Machine Learning models in Python using the supervised and unsupervised learning methods * Learn how to use Apache Spark for processing Big Data efficiently Who This Book Is For If 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 Learn * Learn how to clean your data and ready it for analysis * Implement the popular clustering and regression methods in Python * Train efficient machine learning models using decision trees and random forests * Visualize the results of your analysis using Python's Matplotlib library * Use Apache Spark's MLlib package to perform machine learning on large datasets In Detail 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. Style and approach This 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.

Frank Kane's hands-on Spark training course, based on his bestselling Taming Big Data with Apache Spark and Python video, now available in a book. Understand and analyze large data sets using Spark on a single system or on a cluster. About This Book * Understand how Spark can be distributed across computing clusters * Develop and run Spark jobs efficiently using Python * A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with Spark Who This Book Is For If you are a data scientist or data analyst who wants to learn Big Data processing using Apache Spark and Python, this book is for you. If you have some programming experience in Python, and want to learn how to process large amounts of data using Apache Spark, Frank Kane's Taming Big Data with Apache Spark and Python will also help you. What You Will Learn * Find out how you can identify Big Data problems as Spark problems * Install and run Apache Spark on your computer or on a cluster * Analyze large data sets across many CPUs using Spark's Resilient Distributed Datasets * Implement machine learning on Spark using the MLlib library * Process continuous streams of data in real time using the Spark streaming module * Perform complex network analysis using Spark's GraphX library * Use Amazon's Elastic MapReduce service to run your Spark jobs on a cluster In Detail Frank Kane's Taming Big Data with Apache Spark and Python is your companion to learning Apache Spark in a hands-on manner. Frank will start you off by teaching you how to set up Spark on a single system or on a cluster, and you'll soon move on to analyzing large data sets using Spark RDD, and developing and running effective Spark jobs quickly using Python. Apache Spark has emerged as the next big thing in the Big Data domain - quickly rising from an ascending technology to an established superstar in just a matter of years. Spark allows you to quickly extract actionable insights from large amounts of data, on a real-time basis, making it an essential tool in many modern businesses. Frank has packed this book with over 15 interactive, fun-filled examples relevant to the real world, and he will empower you to understand the Spark ecosystem and implement production-grade real-time Spark projects with ease. Style and approach Frank Kane's Taming Big Data with Apache Spark and Python is a hands-on tutorial with over 15 real-world examples carefully explained by Frank in a step-by-step manner. The examples vary in complexity, and you can move through them at your own pace.

Armchair fiction presents extra large paperback editions of the best in classic Mystery-Crime novels. This hard-nosed tale, "Dead Weight," was penned by well-known mystery-crime writer, Frank Kane. "Get in my way and I'll stamp you flat " That's what the boss of Chinese Heaven told Johnny Liddell. "You'll tell me what I want to know-sooner or later." The gunman swept the flat of the barrel across Johnny's cheek. "You asked for it, peeper... We'll see how tough you are." A switch knife flashed in the goon's hand. Everyone was threatening Johnny Liddell, even his girl and the cops, until Johnny came up with a new kind of twist to trap a killer. It was so good that he fooled everyone-even himself Carried out in the heart of Chinatown, this gritty mystery has it all: Torture, murder, conspiracy... A must read for all Yellow Peril fans and a definite hit-in more ways than one-for any whodunit enthusiast

"A case of corpses. They piled up so fast that private eye Johnny Liddell figured he was ahead if he found them while they were still warm. It started when he was hired as a baby-sitter to a wildcat. She was blonde and beautiful, and stacked better than a deck of marked cards. And she had a cool $200,000 worth of hot diamonds. There was just one hitch. She used bourbon instead of perfume."

"A case of corpses. They piled up so fast that private eye Johnny Liddell figured he was ahead if he found them while they were still warm. It started when he was hired as a baby-sitter to a wildcat. She was blonde and beautiful, and stacked better than a deck of marked cards. And she had a cool $200,000 worth of hot diamonds. There was just one hitch. She used bourbon instead of perfume."