Название: Data Literacy With PythonАвтор: Oswald Campesato
Издательство: Mercury Learning and Information
Год: 2024
Страниц: 271
Язык: английский
Формат: pdf (true)
Размер: 14.6 MB
The purpose of this book is to usher readers into the world of data, ensuring a comprehensive understanding of its nuances, intricacies, and complexities. With Python 3 as the primary medium, the book underscores the pivotal role of data in modernindustries, and how its adept management can lead to insightful decision-making. The book provides a quick introduction to foundational data-related tasks, priming the readers for more advanced concepts of model training introduced later on. Through detailed, step-by-step Python code examples, the reader will master training models, beginning with the kNN algorithm, and then smoothly transitioning to other classifiers, by tweaking mere lines of code. Tools like Sweetviz, Skimpy, Matplotlib, and Seaborn are introduced, offering readers a hands-on experience in rendering charts and graphs. Companion files with source code and data sets are available by writing to the publisher.
At its heart, the book provides a swift introduction to foundational data-related tasks, priming the readers for more advanced concepts of model training introduced later on. Through detailed, step-by-step Python code examples, the readers will traverse the journey of training models, beginning with the kNN algorithm, and then smoothly transitioning to other classifiers, effortlessly, by tweaking mere lines of code.
To derive the maximum value from this book, a foundational grasp of Python 3.x is requisite. While some sections might necessitate a preliminary understanding of the ‘awk’ utility, the majority of the content is dedicated to Python’s prowess. Familiarity with Pandas, especially its data frames, will further enhance the reader’s journey.
Features:
Introduces tools like Sweetviz, Skimpy, Matplotlib, and Seaborn offering readers a hands-on experience in rendering charts and graphs
Companion files with numerous Python code samples
Designed for individuals beginning their foray into Machine Learning, the language caters to a global audience. By intentionally steering clear of colloquialisms, and adopting a standard English approach, it ensures content clarity for readers, irrespective of their linguistic backgrounds.
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