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{ "item_title" : "Fundamentals of Data Science", "item_author" : [" Swapnili Karmore "], "item_description" : "This comprehensive textbook provides a systematic introduction to Data Science, covering the complete lifecycle from data collection to model deployment. Designed for undergraduate and postgraduate students, as well as professionals seeking to enter the field of data science, the book bridges theoretical foundations with practical applications using industry-standard tools and techniques. The book is organized into five carefully structured chapters that progressively build the reader's knowledge and skills. Beginning with an exploration of the evolution and scope of data science, the text guides readers through data collection strategies, pre-processing techniques, exploratory data analysis, statistical methods, model development using regression techniques, and comprehensive model evaluation approaches. Key Features: Comprehensive Coverage: Covers the entire data science pipeline, including data collection, cleaning, transformation, analysis, modeling, and evaluation.Mathematical Foundations: Includes detailed mathematical formulations and statistical concepts essential for understanding data science algorithms.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/6/20/929/770/6209297706_b.jpg", "price_data" : { "retail_price" : "70.64", "online_price" : "70.64", "our_price" : "70.64", "club_price" : "70.64", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Fundamentals of Data Science|Swapnili Karmore

Fundamentals of Data Science : From Data Collection to Model Evaluation

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Overview

This comprehensive textbook provides a systematic introduction to Data Science, covering the complete lifecycle from data collection to model deployment. Designed for undergraduate and postgraduate students, as well as professionals seeking to enter the field of data science, the book bridges theoretical foundations with practical applications using industry-standard tools and techniques. The book is organized into five carefully structured chapters that progressively build the reader's knowledge and skills. Beginning with an exploration of the evolution and scope of data science, the text guides readers through data collection strategies, pre-processing techniques, exploratory data analysis, statistical methods, model development using regression techniques, and comprehensive model evaluation approaches. Key Features: Comprehensive Coverage: Covers the entire data science pipeline, including data collection, cleaning, transformation, analysis, modeling, and evaluation.Mathematical Foundations: Includes detailed mathematical formulations and statistical concepts essential for understanding data science algorithms.

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Details

  • ISBN-13: 9786209297700
  • ISBN-10: 6209297706
  • Publisher: LAP Lambert Academic Publishing
  • Publish Date: February 2026
  • Dimensions: 9 x 6 x 0.28 inches
  • Shipping Weight: 0.36 pounds
  • Page Count: 116

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