"Advanced Data Analytics Using Python" by Sayan Mukhopadhyay and Pratip Samanta is a comprehensive guide for those looking to deepen their knowledge of data analytics using the powerful capabilities of the Python programming language.
This book is designed for experienced data analysts and professionals who want to master advanced data analytics techniques, such as machine learning, big data processing, and result visualization. The authors provide a wide range of examples, covering both traditional statistical methods and modern techniques like neural networks and deep learning.
By reading this book, you will be able to expand your knowledge, improve your skills in working with large datasets, and learn how to solve real-world problems. Download "Advanced Data Analytics Using Python" today and start using powerful data analysis tools to advance your career!
Who Should Read "Advanced Data Analytics Using Python: with machine learning, deep learning and nlp examples"?
- Data analysts: This book will be an excellent resource for those wanting to deepen their knowledge of advanced data analytics and apply Python to solve complex problems.
- Machine learning engineers: Ideal for those already working in machine learning who want to expand their skills in data analysis and modeling.
- Software developers: Useful for developers working with big data and creating machine learning models using Python.
- Students and researchers: A valuable resource for students studying data analysis and researchers tackling scientific and technical problems.
What Makes this Edition Different from Other Data Science Books?
"Advanced Data Analytics Using Python" stands out due to its deep dive into advanced data analytics techniques and machine learning. The authors take a systematic approach to teaching complex analytical methods that go beyond basic analysis. The book covers not only traditional statistical methods, such as regression and clustering, but also modern approaches like neural networks, deep learning, and big data processing.
A key advantage of this edition is its focus on solving real-world problems. Each topic is accompanied by detailed Python code examples, allowing readers to apply their newly gained knowledge immediately.
Moreover, the authors discuss performance optimization and offer techniques for working with large datasets, which is particularly relevant in today’s data-driven world.
More About the Author of the Book
FAQ for "Advanced Data Analytics Using Python"
Is the book suitable for beginner data professionals?
It is aimed at experienced professionals who already have a foundational understanding of data analytics. Beginners are advised to first explore basic concepts before moving on to this book.
What technologies and tools are covered in the book?
The book covers tools like Python libraries for data analysis (Pandas, NumPy), machine learning tools (Scikit-learn), and big data tools such as PySpark.
Does the book include code examples?
Yes, it includes many Python code examples to help readers better understand the theoretical concepts and apply them in practice.
What machine learning methods do the authors cover?
The authors cover a wide range of methods, including regression, clustering, neural networks, deep learning, and ensemble methods such as random forests and boosting.
Does Advanced Data Analytics Using Python cover working with big data?
Yes, the book discusses working with large datasets, including performance optimization techniques and the use of PySpark for big data processing.
Can the book be used for self-study?
Yes, it is suitable for self-study, offering detailed code examples and exercises that can be completed independently.
Does the book cover data visualization?
Yes, the authors emphasize the importance of data visualization and use Python libraries such as Matplotlib and Seaborn to present analytical results.
Information
| Author: | Sayan Mukhopadhyay, Pratip Samanta | Language: | English |
| Publisher: | Apress; 2nd ed. edition | ISBN-13: | 978-1484280041 |
| Publication Date: | November 26, 2022 | ISBN-10: | 1484280040 |
| Print Length: | 268 pages | Category: | JavaScript Books |
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