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13218127
Data Science from Scratch: First Principles with Python
88% of respondents would recommend this to a friend
แแ แแแฃแแแก #:
13218127
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What Stands Out
Comprehensive Foundation
Covers essential principles of data science, making it suitable for beginners who want to grasp concepts from the ground up using Python programming.
Practical Application
Includes hands-on projects and examples, allowing readers to apply theory directly, enhancing understanding and retention of data science techniques.
Updated Content
The second edition features the latest trends and tools in data science, ensuring that readers gain relevant skills applicable in todayโs job market.
แฒแ แแแฃแฅแขแแก แแฆแฌแแ แแแแแ
- Updated for Python 3.6, this second edition of Data Science from Scratch focuses on mastering data science tools and understanding the principles underlying them
- Authored by Joel Grus, the book is designed to help readers with mathematics, statistics, and programming skills to get started as a data scientist
- Includes new material on deep learning, statistics, and natural language processing
- Provides a crash course in Python and covers the basics of linear algebra, statistics, and probability as used in data science
- Teaches how to collect, explore, clean, and manipulate data, as well as dive into the fundamentals of machine learning and implement various models
- Covers topics like recommender systems, natural language processing, network analysis, MapReduce, and databases
| Publisher | O'Reilly Media |
| Publication date | June 11, 2019 |
| Edition | 2nd |
| Language | English |
| Print length | 403 pages |
| ISBN-10 | 1492041130 |
| ISBN-13 | 978-1492041139 |
| Item Weight | 1.57 pounds (710 grams) |
| Dimensions | 6.9 x 0.9 x 9.1 inches (17.5 x 2.3 x 23.1 cm) |
Who Should Buy?
-
Beginner Data Scientists
Ideal for individuals new to data science and programming, providing foundational knowledge and practical Python applications.
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Self-Learners
Great for self-taught learners looking to deepen their understanding of data science concepts through hands-on coding examples.
-
Python Enthusiasts
Perfect for those familiar with Python who want to explore data science topics using a programming-first approach.
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Advanced Practitioners
Not suitable for experienced data scientists seeking advanced techniques or specialized methods beyond core concepts.
แแ แแแฃแฅแขแแก แแฆแฌแแ แแแแแ
Data Science from Scratch: First Principles with Python
About This Item
Are you interested in diving into the world of data science with Python? Look no further than "Data Science from Scratch: First Principles with Python 2nd Edition." This book is perfect for beginners who want to learn Python data science principles and techniques. Whether you're a student, a professional looking to upskill, or someone who simply has a passion for data analysis, this book is a must-have. The second edition offers updated material and a comprehensive introduction to data science concepts using Python. Learn how to harness the power of Python to extract insights from data and uncover patterns that will drive decision-making. With easy-to-follow explanations and step-by-step examples, you'll quickly gain a solid foundation in Python data science. The book covers a wide range of topics, including data visualization, statistical analysis, machine learning, and much more.
With its hands-on approach, you'll not only understand the theory behind data science but also apply it to real-world projects. Whether you're a complete beginner or already have some experience with Python, "Data Science from Scratch: First Principles with Python 2nd Edition" is written in a way that makes complex concepts accessible. You'll feel confident in your ability to tackle data science problems head-on. So, if you're ready to unlock the potential of Python for data science, order your copy of "Data Science from Scratch: First Principles with Python 2nd Edition" today. Start your journey to becoming a proficient Python data scientist and gain the skills needed to succeed in this rapidly growing field.
แแแฅแแ แ แแแแ แจแแแแแฎแแ? แแแแแแแ แแแ แฉแแแจแ
แแแแฎแแแ แแแแแแ แแแแฎแแแแ แแ แแแกแฃแฎแแแ
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แแแแฎแแ:
What topics are covered in Data Science from Scratch: First Principles with Python 2nd Edition?
แแแกแฃแฎแ: This book covers a comprehensive range of topics essential for understanding data science, including statistics, data analysis, machine learning, and algorithm development. Readers will explore foundational concepts such as data representation, data cleaning, visualization techniques, and key machine learning algorithms. The insights provided equip readers with practical skills that can be applied in real-world scenarios, making it an excellent resource for both beginners and intermediate learners seeking to solidify their knowledge of data science with Python. -
แแแแฎแแ:
Who is the author of Data Science from Scratch: First Principles with Python 2nd Edition?
แแแกแฃแฎแ: Data Science from Scratch: First Principles with Python 2nd Edition is authored by Joel Grus, a data scientist and educator. His expertise in the field and clear, engaging writing style make complex topics accessible to a broad audience. Grus combines theoretical insights with practical programming examples, which helps learners to not just understand concepts but also apply them effectively in their own projects and analyses. -
แแแแฎแแ:
Is prior programming knowledge necessary to understand this book?
แแแกแฃแฎแ: While prior programming knowledge can be beneficial, it is not strictly necessary to grasp the concepts in this book. The author explains basic Python programming principles before delving into more complex data science topics. This approach makes the book suitable for readers who may have limited coding experience yet are eager to learn about data science. Beginners will find practical exercises that reinforce learning and facilitate skill development. -
แแแแฎแแ:
Can I use this book to learn data science for machine learning purposes?
แแแกแฃแฎแ: Absolutely! Data Science from Scratch: First Principles with Python 2nd Edition provides a strong foundation in machine learning concepts and techniques. It includes a thorough exploration of algorithms like linear regression, decision trees, and neural networks, along with practical coding examples. This allows readers to learn how to implement machine learning models from the ground up, making it ideal for those looking to enter the machine learning field with a solid understanding of the underlying principles. -
แแแแฎแแ:
Does this book contain practical examples and projects?
แแแกแฃแฎแ: Yes, this book is rich in practical examples and coding projects. Each chapter includes hands-on exercises that encourage readers to apply what they've learned to real-world problems. This practical approach ensures that learners not only absorb theoretical knowledge but also develop the ability to implement data science techniques in various contexts, enhancing their problem-solving skills and confidence in tackling data-driven challenges. -
แแแแฎแแ:
What are the prerequisites for reading this book effectively?
แแแกแฃแฎแ: To effectively engage with Data Science from Scratch: First Principles with Python 2nd Edition, it is beneficial to have a basic understanding of mathematics, especially statistics and linear algebra. Familiarity with Python programming would also enhance the learning experience. However, the author explains concepts in a clear and approachable manner, allowing motivated learners to grasp the material even with minimal prior knowledge, making it a thoughtful choice for aspiring data scientists. -
แแแแฎแแ:
Is this book suitable for professionals already in the data science field?
แแแกแฃแฎแ: Yes, this book is suitable for both newcomers and professionals in the data science field. For seasoned practitioners, it serves as a refresher on fundamental concepts and techniques that may have been overlooked in formal education. Additionally, it provides a hands-on approach to coding algorithms from scratch, which can deepen understanding and offer insights for more efficient workflow practices. Professionals will appreciate the blend of theory and practical application. -
แแแแฎแแ:
How does this edition differ from the first edition?
แแแกแฃแฎแ: The 2nd Edition of Data Science from Scratch includes significant updates that enhance its value as a learning resource. It incorporates new content, refined explanations, and additional examples that reflect the latest trends and advancements in the field of data science. The author has also improved the organization and clarity of the material, making it easier for readers to follow along and apply the principles discussed. This ensures readers have the best possible learning experience with up-to-date practices. -
แแแแฎแแ:
What is the learning approach used in the book?
แแแกแฃแฎแ: The learning approach in Data Science from Scratch is centered on a project-based methodology. Each chapter builds on previous content, combining theoretical explanations with hands-on coding exercises that empower readers to develop their own data science projects. Interactive learning is emphasized, where readers engage actively with the material, thereby solidifying their understanding through practice. This method is particularly effective for grasping complex concepts and encourages confident application of skills. -
แแแแฎแแ:
Where can I buy Data Science from Scratch: First Principles with Python 2nd Edition in Georgia?
แแแกแฃแฎแ: You can purchase Data Science from Scratch: First Principles with Python 2nd Edition from Ubuy. Ubuy offers a wide selection of books and educational resources, making it a convenient option for acquiring the title. It's an ideal platform as it facilitates access to learning materials that can help enhance your knowledge and skills in data science.
Statistics Editorial Review
Data Science from Scratch: First Principles with Python is a comprehensive guide designed for those with basic knowledge of Python and math looking to dive into data science. This book encompasses 27 chapters that cover essential concepts such as linear algebra, probability, and algorithms necessary for understanding machine learning. Readers appreciate the author's engaging writing style, his insightful humor, and the way he bridges the gap between theory and practical application. Although the book serves as a great entry point for beginners, some may find the content a bit dense if completely new to programming and math. Additionally, the tutorial on the Twitter API is outdated but still informative for learning API applications.
Customer Reviews & Ratings
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แฒแแแแแแแ
- Great introduction for aspiring data scientists
- Covers fundamental concepts in data science
- Engaging writing style with humor
- Clear explanations of Python coding
- Bridges theory and practical application
- Suitable for both beginners and advanced users
แแแแฃแกแแแ
- The monochrome format may not appeal to everyone
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แแแฎแแกแแแแแแแแแ แแ แฃแแแ แแขแแกแแแแแ
- Master not only the tools, but also understand the principles of data science
- Learn Python, linear algebra, statistics, and probability
- Explore machine learning models and techniques
- Get updated material on deep learning and natural language processing
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