Over 85 recipes to help you complete real-world data science projects in R and Python About This Book Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data Get beyond the theory and implement real-world projects in data science using R and Python Easy-to-follow recipes will help you understand and implement the numerical computing concepts Who This Book Is For If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python. What You Will Learn Learn and understand the installation procedure and environment required for R and Python on various platforms Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python Build a predictive model and an exploratory model Analyze the results of your model and create reports on the acquired data Build various tree-based methods and Build random forest In Detail As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don't. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python. Style and approach This step-by-step guide to data science is full of hands-on examples of real-world data science tasks. Each recipe focuses on a particular task involved in the data science pipeline, ranging from readying the dataset to analytics and visualization
From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems. Preprocess and vectorize text into high-dimensional feature representations Perform document classification and topic modeling Steer the model selection process with visual diagnostics Extract key phrases, named entities, and graph structures to reason about data in text Build a dialog framework to enable chatbots and language-driven interaction Use Spark to scale processing power and neural networks to scale model complexity
It has been called the most dangerous gang in American history. In Los Angeles alone it is responsible for over 100 homicides per year. Although it has fewer than 300 members, it controls a 40,000-strong street army that is eager to advance its agenda. It waves the flag of the Black Hand and its business is murder. Although known on the streets for over fifty years, the Mexican Mafia has flown under the radar of public awareness and has flourished beneath a deep cover of secrecy. Members are forbidden even to acknowledge its existence. For the first time in its history, the Mexican Mafia is now getting the attention it has been striving to avoid. In this briskly written and thoroughly researched book, Tony Rafael looks at the birth and the blood-soaked growth of this criminal enterprise through the eyes of the victims, the dropouts, the cops and DAs on the front lines of the war against the Mexican Mafia. The first book ever published on the subject, Southern Soldiers is a pioneering work that unveils the operations of this California prison gang and describes how it grew from a small clique of inmates into a transnational criminal organization. As the first prison gang ever to project its power beyond prison walls, the Mexican Mafia controls virtually every Hispanic neighborhood in Southern California and is rapidly expanding its influence into the entire Southwest, across the East Coast, and even into Canada. Riding a wave of unchecked immigration and seemingly beyond the reach of law enforcement, the Mexican Mafia is poised to become the Cosa Nostra of twenty-first-century America.
Produced in Italy from the turn of the 20th century, "sword and sandal" or peplum films were well received in the silent era and attained great popularity in the 1960s following the release of Hercules (1959), starring Mr. Universe Steve Reeves. A global craze for Bronze Age fantasy-adventures ensued and the heroic exploits of Hercules, Maciste, Samson and Goliath were soon a mainstay of American drive-ins and second-run theaters (though mainly disparaged by critics). By 1965, the genre was eclipsed by the spaghetti western, yet the 1960s peplum canon continues to inspire Hollywood epics. This filmography provides credits, cast and comments for dozens of films from 1908 through 1990.
The Greatest Teams Never: Sports Memories of Near Misses, Total Messes, and Not-so-magical Moments chronicles the despair and disappointment of 40 remarkable teams that are remembered more for what they didn’t accomplish than their successes. The book revisits some of the most memorable and unbelievable events in the annals of sports, while at the same time recognizing those deemed "second-best" as unofficially great, even if history may never remember them that way. Each chapter comprises teams with similar notoriety and highlights a particular nuance of their ultimate demise. There is the 2007 New England Patriots stunning Super Bowl loss to the NY Giants headlining You Can't Win em All. Among other oddities in sports, the chapter Better Lucky than Good examines the Immaculate Reception and divergent outcomes for the Pittsburgh Steelers and Oakland Raiders after their historic playoff game. Once long-suffering Red Sox and Cubs fans will appreciate the chapter, Wait til Near. Even international teams such as Brazil futbol and the USSR hockey are showcased in C'est La Vie. Using hundreds of quotes from players and coaches, statistics, and “distant” replay the book explores both the promise and improbable ending for some truly great teams. Hear in their own words how several Golden State Warriors blamed themselves for blowing the 2016 NBA finals; that Mickey Mantle and other Yankees greats wouldn’t admit the 1960 world champion Pirates were the better team; heartbroken college athletes who try to make sense of one-loss seasons; and more. From Baby Boomers to Millennials, avid sports fans to casual observers, there is something for anyone who follows sports, played sports, or simply roots for their hometown team. Each chapter is filled with reasons to consider the “losers” as still great and ends with a Claim to Fame providing some level of vindication for players and their fans. After all, everyone deserves a second chance — even the greatest teams never.
The most comprehensive book about the electric guitar. Its A-to-Z format covers more than 120 makers from around the world and details their successes and failures through 1,200 unique color, studio quality photographs.
The surprising story of Che Guevara, Fidel Castro, and the scrappy band of rebel men and women who followed them. Most people are familiar with the basics of the Cuban Revolution of 1956–1959: it was led by two of the twentieth century’s most charismatic figures, Fidel Castro and Che Guevara; it successfully overthrew the island nation’s US–backed dictator; and it quickly went awry under Fidel’s rule. But less is remembered about the amateur nature of the movement or the lives of its players. In this wildly entertaining and meticulously researched account, historian and journalist Tony Perrottet unravels the human drama behind history’s most improbable revolution: a scruffy handful of self-taught revolutionaries—many of them kids just out of college, literature majors, and art students, and including a number of extraordinary women—who defeated 40,000 professional soldiers to overthrow the dictatorship of Fulgencio Batista. Cuba Libre!’s deep dive into the revolution reveals fascinating details: How did Fidel’s highly organized lover Celia Sánchez whip the male guerrillas into shape? Who were the two dozen American volunteers who joined the Cuban rebels? How do you make land mines from condensed milk cans—or, for that matter, cook chorizo à la guerrilla (sausage guerrilla-style)? Cuba Libre! is an absorbing look back at a liberation movement that captured the world's imagination with its spectacular drama, foolhardy bravery, tragedy, and, sometimes, high comedy—and that set the stage for Cold War tensions that pushed the world to the brink of nuclear war.
Life in Fairfield in the decades after World War II was an unparalleled experience. From cruising down Texas Street on weekends to catching a carnival in the Wonder World parking lot, fond memories of long-lost times haven't been forgotten. People flocked to vintage eateries like Joe's Buffet and Smorga Bob's and played on the rocket ship slide at Allan Witt Park. Roller rinks like the M&M Skateway hosted not only skaters but also dances featuring Fats Domino and Roy Orbison. Commuters hopped aboard the FART bus to save on gas, and frequenting Dave's Giant Hamburgers was a rite of passage. Longtime Daily Republic columnist and accidental historian Tony Wade takes a deep dive into the Fairfield of yesteryear.
Over 85 recipes to help you complete real-world data science projects in R and PythonAbout This Book* Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data* Get beyond the theory and implement real-world projects in data science using R and Python* Easy-to-follow recipes will help you understand and implement the numerical computing conceptsWho This Book Is ForIf you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python.What You Will Learn* Learn and understand the installation procedure and environment required for R and Python on various platforms* Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python* Build a predictive model and an exploratory model* Analyze the results of your model and create reports on the acquired data* Build various tree-based methods and Build random forestIn DetailAs increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don't. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use.Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis--R and Python.Style and approachThis step-by-step guide to data science is full of hands-on examples of real-world data science tasks. Each recipe focuses on a particular task involved in the data science pipeline, ranging from readying the dataset to analytics and visualization
Over 85 recipes to help you complete real-world data science projects in R and Python About This Book Tackle every step in the data science pipeline and use it to acquire, clean, analyze, and visualize your data Get beyond the theory and implement real-world projects in data science using R and Python Easy-to-follow recipes will help you understand and implement the numerical computing concepts Who This Book Is For If you are an aspiring data scientist who wants to learn data science and numerical programming concepts through hands-on, real-world project examples, this is the book for you. Whether you are brand new to data science or you are a seasoned expert, you will benefit from learning about the structure of real-world data science projects and the programming examples in R and Python. What You Will Learn Learn and understand the installation procedure and environment required for R and Python on various platforms Prepare data for analysis by implement various data science concepts such as acquisition, cleaning and munging through R and Python Build a predictive model and an exploratory model Analyze the results of your model and create reports on the acquired data Build various tree-based methods and Build random forest In Detail As increasing amounts of data are generated each year, the need to analyze and create value out of it is more important than ever. Companies that know what to do with their data and how to do it well will have a competitive advantage over companies that don't. Because of this, there will be an increasing demand for people that possess both the analytical and technical abilities to extract valuable insights from data and create valuable solutions that put those insights to use. Starting with the basics, this book covers how to set up your numerical programming environment, introduces you to the data science pipeline, and guides you through several data projects in a step-by-step format. By sequentially working through the steps in each chapter, you will quickly familiarize yourself with the process and learn how to apply it to a variety of situations with examples using the two most popular programming languages for data analysis—R and Python. Style and approach This step-by-step guide to data science is full of hands-on examples of real-world data science tasks. Each recipe focuses on a particular task involved in the data science pipeline, ranging from readying the dataset to analytics and visualization
From news and speeches to informal chatter on social media, natural language is one of the richest and most underutilized sources of data. Not only does it come in a constant stream, always changing and adapting in context; it also contains information that is not conveyed by traditional data sources. The key to unlocking natural language is through the creative application of text analytics. This practical book presents a data scientist’s approach to building language-aware products with applied machine learning. You’ll learn robust, repeatable, and scalable techniques for text analysis with Python, including contextual and linguistic feature engineering, vectorization, classification, topic modeling, entity resolution, graph analysis, and visual steering. By the end of the book, you’ll be equipped with practical methods to solve any number of complex real-world problems. Preprocess and vectorize text into high-dimensional feature representations Perform document classification and topic modeling Steer the model selection process with visual diagnostics Extract key phrases, named entities, and graph structures to reason about data in text Build a dialog framework to enable chatbots and language-driven interaction Use Spark to scale processing power and neural networks to scale model complexity
In an ideal universe, theirs might have been the perfect love story from two separate worlds. But in the heart of the Bible Belt South, in America of the mid-twentieth century, their young love was forbidden because of their skin color. She was white, lovely, and privileged, growing up in a Tara-like Victorian home. He was Latino, dark-skinned, and working class--the grandson of a Mexican revolutionary who had fought with Pancho Villa. And an innocent waltz at a school May Fete--a waltz that they were not permitted to dance together--came to symbolize their society's racial divide. In The Prince of South Waco, author Tony Castro narrates his sensitive rite-of-passage memoir of growing up Latino in the segregated South in an age when being different in America often brought the cruel, hard reality of the time, along with heartbreak and despair. He recounts how, as a child in an era before bilingual education and affirmative action, he overcame speech and learning disabilities and an inability to speak English to become an honor student with a penchant for literature, the classics, and writing. Throughout his youth, he remained discreetly close to the teenage ballerina who had captured his heart. All the while, he encountered ugly warnings of violence and harm--against the two of them--should they see each other and defy the ages-old prohibition in the South against interracial relationships. A story taking place before the enactment of civil rights legislation, The Prince of South Waco provides insight into the issue of racial discrimination and hate of the times. Critical Acclaim for Tony Castro's The Prince of South Waco: American Dreams and Great Expectations "Readers who step into Tony's Time Machine, The Prince of South Waco, are in for a thrilling, lyrical ride, a true tale of romantic woes and raucous rebellion that will break readers' hearts. Castro's coming-of-age story is a painfully poignant memoir of romance, racism and self-discovery fraught with recollections of lynchings, Jim Crow-ism, no-white-girl speeches, growing up Chicano and excelling as one of the best and brightest of emerging young journalists of his time. 'How do you reclaim your destiny when it has been so connected with a love that has been lost?' asks the author. And therein lies this soulful impasse." Preston F. Kirk, formerly of United Press International, Houston "Tony Castro's honest and powerful memoir captures the essential American story of the struggle for cultural assimilation. The very best stories are written in blood, and in Castro's finely woven personal narrative, the reader can almost feel his heart beating." Bob Vickrey Contributing columnist, The Waco Tribune-Herald
This will help us customize your experience to showcase the most relevant content to your age group
Please select from below
Login
Not registered?
Sign up
Already registered?
Success – Your message will goes here
We'd love to hear from you!
Thank you for visiting our website. Would you like to provide feedback on how we could improve your experience?
This site does not use any third party cookies with one exception — it uses cookies from Google to deliver its services and to analyze traffic.Learn More.