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- Author: Oswald Campesato
- Publisher: Mercury Learning and Information
- ISBN-10: 1501521993
- ISBN-13: 9781501521997
- Format: 17.8 x 22.9 x 1.5 cm, minkšti viršeliai
- Language: English
- SAVE -10% with code: EXTRA
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Description
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.
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
EXTRA 10 % discount with code: EXTRA
The promotion ends in 22d.23:42:50
The discount code is valid when purchasing from 10 €. Discounts do not stack.
- Author: Oswald Campesato
- Publisher: Mercury Learning and Information
- ISBN-10: 1501521993
- ISBN-13: 9781501521997
- Format: 17.8 x 22.9 x 1.5 cm, minkšti viršeliai
- Language: English English
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.
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
Reviews