Data wrangling : concepts, applications and tools /
Data wrangling : concepts, applications and tools /
edited by M. Niranjanamurthy, Kavita Sheoran, Geetika Dhand, and Prabhjot Kaur.
- 1 online resource
Includes bibliographical references and index.
Basic Principles of Data Wrangling / Akshay Singh, Surender Singh, Jyotsna Rathee -- Skills and Responsibilities of Data Wrangler / Prabhjot Kaur, Anupama Kaushik, Aditya Kapoor -- Data Wrangling Dynamics / Simarjit Kaur, Anju Bala, Anupam Garg -- Essentials of Data Wrangling / Menal Dahiya, Nikita Malik, Sakshi Rana -- Data Leakage and Data Wrangling in Machine Learning for Medical Treatment / P.T. Jamuna Devi, B.R. Kavitha -- Importance of Data Wrangling in Industry 4.0 / Rachna Jain, Geetika Dhand, Kavita Sheoran, Nisha Aggarwal -- Managing Data Structure in R / Mittal Desai, Chetan Dudhagara -- Dimension Reduction Techniques in Distributional Semantics: An Application Specific Review / Pooja Kherwa, Jyoti Khurana, Rahul Budhraj, Sakshi Gill, Shreyansh Sharma, Sonia Rathee -- Big Data Analytics in Real Time for Enterprise Applications to Produce Useful Intelligence / Prashant Vats, Siddhartha Sankar Biswas -- Generative Adversarial Networks: A Comprehensive Review / Jyoti Arora, Meena Tushir, Pooja Kherwa, Sonia Rathee -- Analysis of Machine Learning Frameworks Used in Image Processing: A Review / Gurpreet Kaur, Kamaljit Singh Saini -- Use and Application of Artificial Intelligence in Accounting and Finance: Benefits and Challenges / Ram Singh, Rohit Bansal, M. Niranjanamurthy -- Obstacle Avoidance Simulation and Real-Time Lane Detection for AI-Based Self-Driving Car / B. Eshwar, Harshaditya Sheoran, Shivansh Pathak, Meena Rao -- Impact of Suppliers Network on SCM of Indian Auto Industry: A Case of Maruti Suzuki India Limited / Ruchika Pharswan, Ashish Negi, Tridib Basak.
Written and edited by some of the world's top experts in the field, this exciting new volume provides state-of-the-art research and latest technological breakthroughs in data wrangling, its theoretical concepts, practical applications, and tools for solving everyday problems. Data wrangling is the process of cleaning and unifying messy and complex data sets for easy access and analysis. This process typically includes manually converting and mapping data from one raw form into another format to allow for more convenient consumption and organization of the data. Data wrangling is increasingly ubiquitous at today's top firms. Data cleaning focuses on removing inaccurate data from your data set whereas data wrangling focuses on transforming the data's format, typically by converting "raw" data into another format more suitable for use. Data wrangling is a necessary component of any business. Data wrangling solutions are specifically designed and architected to handle diverse, complex data at any scale, including many applications, such as Datameer, Infogix, Paxata, Talend, Tamr, TMMData, and Trifacta. This book synthesizes the processes of data wrangling into a comprehensive overview, with a strong focus on recent and rapidly evolving agile analytic processes in data-driven enterprises, for businesses and other enterprises to use to find solutions for their everyday problems and practical applications. Whether for the veteran engineer, scientist, or other industry professional, this book is a must have for any library.
9781119879862 1119879868 9781119879855 111987985X
9781119879688 O'Reilly Media
Data mining.
Data editing.
Data sets.
Exploration de donn�ees (Informatique)
Data mining
QA76.9.D345 / D38 2023
006.3/12
Includes bibliographical references and index.
Basic Principles of Data Wrangling / Akshay Singh, Surender Singh, Jyotsna Rathee -- Skills and Responsibilities of Data Wrangler / Prabhjot Kaur, Anupama Kaushik, Aditya Kapoor -- Data Wrangling Dynamics / Simarjit Kaur, Anju Bala, Anupam Garg -- Essentials of Data Wrangling / Menal Dahiya, Nikita Malik, Sakshi Rana -- Data Leakage and Data Wrangling in Machine Learning for Medical Treatment / P.T. Jamuna Devi, B.R. Kavitha -- Importance of Data Wrangling in Industry 4.0 / Rachna Jain, Geetika Dhand, Kavita Sheoran, Nisha Aggarwal -- Managing Data Structure in R / Mittal Desai, Chetan Dudhagara -- Dimension Reduction Techniques in Distributional Semantics: An Application Specific Review / Pooja Kherwa, Jyoti Khurana, Rahul Budhraj, Sakshi Gill, Shreyansh Sharma, Sonia Rathee -- Big Data Analytics in Real Time for Enterprise Applications to Produce Useful Intelligence / Prashant Vats, Siddhartha Sankar Biswas -- Generative Adversarial Networks: A Comprehensive Review / Jyoti Arora, Meena Tushir, Pooja Kherwa, Sonia Rathee -- Analysis of Machine Learning Frameworks Used in Image Processing: A Review / Gurpreet Kaur, Kamaljit Singh Saini -- Use and Application of Artificial Intelligence in Accounting and Finance: Benefits and Challenges / Ram Singh, Rohit Bansal, M. Niranjanamurthy -- Obstacle Avoidance Simulation and Real-Time Lane Detection for AI-Based Self-Driving Car / B. Eshwar, Harshaditya Sheoran, Shivansh Pathak, Meena Rao -- Impact of Suppliers Network on SCM of Indian Auto Industry: A Case of Maruti Suzuki India Limited / Ruchika Pharswan, Ashish Negi, Tridib Basak.
Written and edited by some of the world's top experts in the field, this exciting new volume provides state-of-the-art research and latest technological breakthroughs in data wrangling, its theoretical concepts, practical applications, and tools for solving everyday problems. Data wrangling is the process of cleaning and unifying messy and complex data sets for easy access and analysis. This process typically includes manually converting and mapping data from one raw form into another format to allow for more convenient consumption and organization of the data. Data wrangling is increasingly ubiquitous at today's top firms. Data cleaning focuses on removing inaccurate data from your data set whereas data wrangling focuses on transforming the data's format, typically by converting "raw" data into another format more suitable for use. Data wrangling is a necessary component of any business. Data wrangling solutions are specifically designed and architected to handle diverse, complex data at any scale, including many applications, such as Datameer, Infogix, Paxata, Talend, Tamr, TMMData, and Trifacta. This book synthesizes the processes of data wrangling into a comprehensive overview, with a strong focus on recent and rapidly evolving agile analytic processes in data-driven enterprises, for businesses and other enterprises to use to find solutions for their everyday problems and practical applications. Whether for the veteran engineer, scientist, or other industry professional, this book is a must have for any library.
9781119879862 1119879868 9781119879855 111987985X
9781119879688 O'Reilly Media
Data mining.
Data editing.
Data sets.
Exploration de donn�ees (Informatique)
Data mining
QA76.9.D345 / D38 2023
006.3/12
