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.

A tense, searing novel of treachery, love and intrigue on a private yacht—destination unknown! Three desperate men and two fiery woman who gambles everything they had in a deadly game of winner-take-all. From the swift, sharp pen of Frank Kane, writer of the Johnny Liddell mystery series comes a breathtaking crashing tale of adventure and suspense.

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.

Everyone was threatening Johnny Liddell—even his girl, and the cops—until Johnny came up with a new twist to trap a killer. It was so good he fooled everyone—even himself!

In Stacked Deck, Johnny Liddell finds himself in a game where the stakes are murder and the cards are all marked against him. When a routine investigation into a crooked gambling ring turns deadly, Liddell is drawn into a world where the winners cheat, the losers wind up dead, and everyone's playing an angle. As the bodies pile up, he has to figure out who's stacking the deck—and why—before he becomes the next victim in a dangerous game he never agreed to play. Frank Kane delivers another razor-sharp noir thriller, rich with smoky backroom poker games, glitzy nightclubs masking criminal enterprises, and a steady stream of suspects who all seem to have something to hide. Liddell, with his trademark wisecracks and stubborn streak, moves through a labyrinth of conmen, cardsharps, and molls whose loyalties change with the turn of a card. Each lead opens new risks, and each clue takes him closer to a truth more dangerous than the lies. With snappy dialogue, breakneck pacing, and a hardboiled atmosphere steeped in postwar urban grit, Stacked Deck is a prime example of mid-century pulp fiction at its most compelling. For fans of the genre, it's a high-tension ride where the odds are against the hero—but in Johnny Liddell's world, that's just the way he likes it.

Every time Johnny Liddell tried to keep a date with his blond, beautiful, and famous client, the whole neighborhood got sprayed with machine-gun bullets. Sometimes, Johnny figured, it didn’t pay to get out of bed—especially when it was filled with a willing companion ... and the cops yelled murder when he killed a couple of hoods who’d been trying to shoot him full of holes.

A Hollywood pool party. A beautiful woman. And Johnny Liddell. It all adds up to a mystery!

"P.I. Johnny Liddell tangles with mobsters, molls -- and murder! ""...the [Johnny Liddell] books are classic examples of the hard-boiled private eye formula...[The] books are often distinguished by a gritty, authentic portrayal of New York cops and their methods..."" —St. James Guide to Crime and Mystery Writers"

Following the collapse of his business and the loss of his home, Frank Kane made a catastrophic decision. In desperation, he agreed to smuggle cocaine out of Venezuela. Almost inevitably, he and his girlfriend, Sam, were caught. The price they paid was a ten-year sentence in the hell of the overcrowded Venezuelan prison system, notorious for corruption and abuse, and rife with weapons and gangs. At one point, Frank was held in the remote El Dorado prison, better known for being the one-time home of Henri Charrière, or Papillon. He witnessed countless murders as gang leaders fought for power, and he had to become as ruthless as his fellow inmates in order to survive. In an attempt to dull the reality of the horrendous conditions, he succumbed to drugs. After enduring years of systematic beatings by the guards and attempts on his life by inmates, Frank suffered more than one breakdown. He lost over four stone and was riddled with disease, but somehow he found the strength within himself to survive and was eventually released in 2004 after serving over seven years of his sentence. During the long walk back from hell, Frank decided to tell his story.

Johnny Liddell visits New Orleans, where he finds wine, women -- and poisons unknown!