Sarkar Tirthajyoti (60 results)

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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.

paperback. Condition: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority.

paperback. Condition: Fine. Clean Pages. Proceeds benefit the Pima County Public Library system, which serves Tucson and southern Arizona.

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Condition: New. The Data Wrangling Workshop, Second Edition: Create your own actionable insights using data from multiple raw sources (Paperback or Softback).

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Paperback. Condition: New. This book focuses on the Python-based tools and techniques to help you become highly productive at all aspects of typical data science stacks such as statistical analysis, visualization, model selection, and feature engineering.You'll review the inefficiencies and bottlenecks lurking in the daily business process and solve them with practical solutions. Automation of repetitive data science tasks is a key mindset that is promoted throughout the book. You'll learn how to extend the existing coding practice to handle larger datasets with high efficiency with the help of advanced libraries and packages that already exist in the Python ecosystem. The book focuses on topics such as how to measure the memory footprint and execution speed of machine learning models, quality test a data science pipelines, and modularizing a data science pipeline for app development. You'll review Python libraries which come in very handy for automating and speeding up the day-to-day tasks.  In the end, you'll understand and perform data science and machine learning tasks beyond the traditional methods and utilize the full spectrum of the Python data science ecosystem to increase productivity.  What You'll Learn Write fast and efficient code for data science and machine learningBuild robust and expressive data science pipelinesMeasure memory and CPU profile for machine learning methodsUtilize the full potential of GPU for data science tasks Handle large and complex data sets efficiently Who This Book Is For Data scientists, data analysts, machine learning engineers, Artificial intelligence practitioners, statisticians who want to take full advantage of Python ecosystem.…

Taschenbuch. Condition: Neu. Neuware - What if you decided never to stay anywhere long enough to become trapped by it In California of the 1980s and early 1990s-a world of changing cities, fading countercultures, new technologies, economic shifts, and uneasy reinvention-August Wren lives by a simple rule: one job, one year, then move on. From the docks of San Francisco to vineyards, classrooms, radio stations, deserts, and mountain towns, he keeps changing work, places, and relationships before any of them can fully claim him.But every year leaves something behind.The Wren Almanac is a literary novel about freedom, memory, love, and the quiet cost of always moving on. Set against a changing California, it follows a man who believes a life can be built from departures-and slowly begins to question whether leaving is truly the same thing as being free.For readers who enjoy reflective, character-driven fiction about time, place, choice, and regret.…

Paperback. Condition: New.

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Paperback. Condition: New. This book focuses on the Python-based tools and techniques to help you become highly productive at all aspects of typical data science stacks such as statistical analysis, visualization, model selection, and feature engineering.You'll review the inefficiencies and bottlenecks lurking in the daily business process and solve them with practical solutions. Automation of repetitive data science tasks is a key mindset that is promoted throughout the book. You'll learn how to extend the existing coding practice to handle larger datasets with high efficiency with the help of advanced libraries and packages that already exist in the Python ecosystem. The book focuses on topics such as how to measure the memory footprint and execution speed of machine learning models, quality test a data science pipelines, and modularizing a data science pipeline for app development. You'll review Python libraries which come in very handy for automating and speeding up the day-to-day tasks.  In the end, you'll understand and perform data science and machine learning tasks beyond the traditional methods and utilize the full spectrum of the Python data science ecosystem to increase productivity.  What You'll Learn Write fast and efficient code for data science and machine learningBuild robust and expressive data science pipelinesMeasure memory and CPU profile for machine learning methodsUtilize the full potential of GPU for data science tasks Handle large and complex data sets efficiently Who This Book Is For Data scientists, data analysts, machine learning engineers, Artificial intelligence practitioners, statisticians who want to take full advantage of Python ecosystem.…

Condition: New. pp. 460.

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