Summary
Modern data science solutions need to be clean, easy to read, and scalable. In Mastering Large Datasets with Python, author J.T. Wolohan teaches you how to take a small project and scale it up using a functionally influenced approach to Python coding. You'll explore methods and built-in Python tools that lend themselves to clarity and scalability, like the high-performing parallelism method, as well as distributed technologies that allow for high data throughput. The abundant hands-on exercises in this practical tutorial will lock in these essential skills for any large-scale data science project.
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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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Kartoniert / Broschiert. Etat : 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 ite. N° de réf. du vendeur 294137606
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Taschenbuch. Etat : Neu. Neuware - 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 tools 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. N° de réf. du vendeur 9781617296239
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