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Numéro d'article:
101849341
Learning Data Science: Data Wrangling, Exploration, Visualization, and Modeling with Python
Numéro d'article:
101849341
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Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass the entire data science lifecycle.
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Ce qui se démarque
Comprehensive Coverage
This book provides an all-in-one approach to data science, encompassing essential skills from data wrangling to modeling, making it ideal for beginners and intermediate learners seeking a thorough understanding.
Practical Python Focus
With a strong emphasis on Python, the book equips readers with practical coding examples and exercises, empowering them to apply data science concepts effectively in real-world scenarios.
Visualization Techniques
It expertly covers visualization methods, enabling readers to present data insights clearly and effectively, which is crucial for decision-making in any data-driven field.
Détails du produit
- As an aspiring data scientist, you appreciate why organizations rely on data for important decisions—whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of collecting, wrangling, analyzing, and drawing conclusions from data. Learning Data Science is the first book to cover foundational skills in both programming and statistics that encompass this entire lifecycle. It's aimed at those who wish to become data scientists or who already work with data scientists, and at data analysts who wish to cross the technical/nontechnical divide. If you have a basic knowledge of Python programming, you'll learn how to work with data using industry-standard tools like pandas. Refine a question of interest to one that can be studied with data Pursue data collection that may involve text processing, web scraping, etc. Glean valuable insights about data through data cleaning, exploration, and visualization Learn how to use modeling to describe the data Generalize findings beyond the data
| Publisher | O'Reilly Media |
| Publication date | October 24, 2023 |
| Edition | 1st |
| Language | English |
| Print length | 594 pages |
| ISBN-10 | 1098113004 |
| ISBN-13 | 978-1098113001 |
| Item Weight | 2.31 pounds (1.05 kg) |
| Dimensions | 7 x 1.25 x 9.25 inches (17.8 x 3.2 x 23.5 cm) |
À qui est-ce destiné ?
-
Aspiring Data Scientists
Perfect for beginners looking to understand core data science principles using Python through hands-on projects and examples.
-
Students and Academics
Ideal for students studying data analytics or data science who require structured learning and practical applications.
-
Professionals Transitioning Careers
Beneficial for professionals seeking to shift into data-focused roles needing foundational knowledge in data manipulation and analysis.
-
Complete Beginners
Not suitable for those with no prior programming experience as it assumes basic knowledge of Python.
-
Advanced Data Practitioners
Less beneficial for experienced data scientists looking for in-depth techniques or niche specializations beyond foundational concepts.
-
Non-technical Users
Not recommended for individuals without technical skills or interest in programming, as content is code-centric and analytical.
DESCRIPTION DU PRODUIT
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Questions et réponses des clients
-
question:
Do I need prior programming experience to benefit from this book?
répondre: A basic knowledge of Python programming is recommended but not mandatory. -
question:
What kind of tools will I learn to use in this book?
répondre: You will learn to use industry-standard tools such as pandas for data analysis. -
question:
Is this book suitable for someone working in a non-technical role?
répondre: Yes, it is designed for both aspiring data scientists and those in non-technical roles looking to understand data science.
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Caractéristiques et avantages
- Master data science skills to transform raw data into actionable insights.
- Learn programming and statistics foundational skills essential for data scientists.
- Ideal for aspiring data scientists and data analysts seeking to bridge technical gaps.
- Gain proficiency in industry-standard tools like pandas for data manipulation.
- Explore data collection techniques including text processing and web scraping.
- Visualize and model data to draw generalized conclusions and insights.
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