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- Principles of Data Science with Python: Intro...
Principles of Data Science with Python: Introduction to Scientific Computing, Data Analysis, and Data Visualization
MNT 150176
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Unlock the power of data with practical Python programming for scientific computing, data analysis, and visualization.
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What Stands Out
Бүтээгдэхүүний дэлгэрэнгүй мэдээлэл
| Publisher | Arash Karimpour |
| Publication date | July 31, 2020 |
| Language | English |
| Print length | 544 pages |
| ISBN-10 | 1735241008 |
| ISBN-13 | 978-1735241005 |
| Item Weight | 2.53 pounds (1.15 kg) |
| Dimensions | 7.5 x 1.23 x 9.25 inches (19.1 x 3.1 x 23.5 cm) |
Who Should Buy?
-
Aspiring Data Scientists
Ideal for beginners seeking foundational knowledge in data science using Python for practical applications and theoretical insights.
-
Students and Educators
Perfect for academic settings, providing structured lessons and exercises in data analysis and visualization techniques.
-
Professionals Transitioning Fields
Beneficial for individuals switching to data-centric careers, offering essential skills applicable in various industries.
-
Advanced Data Scientists
Not suitable for experts as it may lack advanced techniques and depth required for seasoned professionals.
БАРААНЫ ТАЙЛБАР
Principles of Data Science with Python: Introduction to Scientific Computing, Data Analysis, and Data Visualization
Хэрэглэгчийн асуулт, хариулт
-
Асуулт:
What programming language does the book focus on?
Хариулт: The book focuses on programming with the Python language. -
Асуулт:
Does this book cover machine learning topics?
Хариулт: No, the book does not cover machine learning or artificial intelligence topics. -
Асуулт:
What libraries will I learn about in this book?
Хариулт: You will learn about libraries such as NumPy, Pandas, Matplotlib, and SciPy.
Data Processing Editorial Review
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Product Price History
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MNT 150176
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Онцлог & Давуу талууд
- Learn Python programming for data science applications.
- Master scientific computing and data visualization techniques.
- Explore the functionalities of libraries like NumPy, Pandas, and Matplotlib.
- Understand statistical functions and time-series analysis.
- Gain hands-on experience with interpolation, curve fitting, and numerical integration.
- Focus on practical data manipulation without machine learning or AI content.
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