Sinossi
With an emphasis on clarity, style, and performance, author J.T. Wolohan expertly guides you through implementing a functionally-influenced approach to Python coding. You'll get familiar with Python's functional built-ins like the functools operator and itertools modules, as well as the toolz library.
Mastering Large Datasets teaches you to write easily readable, easily scalable Python code that can efficiently process large volumes of structured and unstructured data. By the end of this comprehensive guide, you'll have a solid grasp on the tools and methods that will take your code beyond the laptop and your data science career to the next level!
Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
Informazioni sugli autori
J.T. Wolohan is a lead data scientist at Booz Allen Hamilton and a PhD researcher at Indiana University, Bloomington, affiliated with the Department of Information and Library Science and the School of Informatics and Computing. His professional work focuses on rapid prototyping and scalable AI. His research focuses on computational analysis of social uses of language online.
J.T. Wolohan is a lead data scientist at Booz Allen Hamilton and a PhD researcher at Indiana University, Bloomington, affiliated with the Department of Information and Library Science and the School of Informatics and Computing. His professional work focuses on rapid prototyping and scalable AI. His research focuses on computational analysis of social uses of language online.
Le informazioni nella sezione "Su questo libro" possono far riferimento a edizioni diverse di questo titolo.
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Paperback. Condizione: New. With an emphasis on clarity, style, and performance, author J.T. Wolohan expertly guides you through implementing a functionally-influenced approach to Python coding. You'll get familiar with Python's functional built-ins like the functools operator and itertools modules, as well as the toolz library. Mastering Large Datasets teaches you to write easily readable, easily scalable Python code that can efficiently process large volumes of structured and unstructured data. By the end of this comprehensive guide, you'll have a solid grasp on the tools and methods that will take your code beyond the laptop and your data science career to the next level!Key features. An introduction to functional and parallel programming . Data science workflow . Profiling code for better performance . Fulfilling different quality objectives for a single unifying task . Python multiprocessing . Practical exercises including full-scale distributed applicationsAudienceReaders should have intermediate Python programming skills.About the technologyPython is a data scientist's dream-come-true, thanks to readily available libraries that support tasks like data analysis, machine learning, visualization, and numerical computing. J.T. Wolohan is a lead data scientist at Booz Allen Hamilton and a PhD researcher at Indiana University, Bloomington, affiliated with the Department of Information and Library Science and the School of Informatics and Computing. His professional work focuses on rapid prototyping and scalable AI. His research focuses on computational analysis of social uses of language online. Codice articolo LU-9781617296239
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Paperback. Condizione: new. Paperback. With an emphasis on clarity, style, and performance, author J.T. Wolohan expertly guides you through implementing a functionally-influenced approach to Python coding. Youll get familiar with Pythons functional built-ins like the functools operator and itertools modules, as well as the toolz library. Mastering Large Datasets teaches you to write easily readable, easily scalable Python code that can efficiently process large volumes of structured and unstructured data. By the end of this comprehensive guide, youll have a solid grasp on the tools and methods that will take your code beyond the laptop and your data science career to the next level!Key features An introduction to functional and parallel programming Data science workflow Profiling code for better performance Fulfilling different quality objectives for a single unifying task Python multiprocessing Practical exercises including full-scale distributed applicationsAudienceReaders should have intermediate Python programming skills.About the technologyPython is a data scientists dream-come-true, thanks to readily available libraries that support tasks like data analysis, machine learning, visualization, and numerical computing. J.T. Wolohan is a lead data scientist at Booz Allen Hamilton and a PhD researcher at Indiana University, Bloomington, affiliated with the Department of Information and Library Science and the School of Informatics and Computing. His professional work focuses on rapid prototyping and scalable AI. His research focuses on computational analysis of social uses of language online. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Codice articolo 9781617296239
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