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88178185
Data Scientist Training Course at the University of Tokyo ~Learn data analysis using your hands in Python~ Tankobon Softcover ― March 14, 2019
90% of respondents would recommend this to a friend
Nº de artículo:
88178185
HNL 821
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This book is like a map and compass for becoming a data scientist.
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What Stands Out
Hands-On Learning
Engage in practical exercises that reinforce data analysis concepts, ensuring a deep understanding of Python applications for real-world data challenges.
Expert Instructors
Learn from experienced professionals at the University of Tokyo, offering insights and mentorship that enhance the educational experience and boost career readiness.
Comprehensive Curriculum
Cover a wide range of data science topics, providing learners with the essential knowledge and skills needed to excel in a competitive job market.
Detalles de producto
| Publisher | u30deu30a4u30cau30d3u51fau7248 |
| Publication date | March 14, 2019 |
| Language | Japanese |
| Print length | 448 pages |
| ISBN-10 | 4839965250 |
| ISBN-13 | 978-4839965259 |
| Item Weight | 600 g |
| Dimensions | 7.24 x 0.98 x 9.21 inches (18.4 x 2.5 x 23.4 cm) |
Who Should Buy?
-
Aspiring Data Scientists
This course is perfect for individuals aiming to kickstart a career in data science and gain practical skills.
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Python Enthusiasts
Ideal for users who are interested in enhancing their Python skills specifically for data analysis purposes.
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Hands-On Learners
Suitable for those who prefer hands-on learning experiences rather than theoretical approaches to data analysis.
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Advanced Practitioners
Not ideal for experts already well-versed in data science, as it may lack advanced content.
DESCRIPCIÓN DEL PRODUCTO
Data Scientist Training Course at the University of Tokyo ~Learn data analysis using your hands in Python~ Tankobon Softcover ― March 14, 2019
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塚本邦尊 , 山田典一 , 大澤文孝 Editorial Review
The editorial review presents a nuanced perspective on the educational value of the book titled "Pythonで手を動かしながら学ぶデータサイエンス". The content is structured to guide readers through the foundational elements of programming, mathematics, machine learning, and deep learning, making it particularly beneficial for beginners. However, while it is comprehensive, some readers feel that the coverage of certain critical machine learning techniques such as Random Forest and Gradient Boosting is lacking, leaving them with a sense of incompleteness, especially those aiming to become proficient machine learning engineers. Readers have reported successfully leveraging the book to set up Google Cloud for execution of linear regression tasks and navigating through the complexities of data science. Even those who Consider themselves complete novices have found it manageable, as long as they possess the drive to delve into additional learning via online resources. The structure of the book encourages logical thinking and problem-solving, which many readers found stimulating. Despite some criticisms regarding the depth of information and the clarity of certain programming implementations, many asserted that the groundwork laid by this book is invaluable for embarking on a professional journey in data science. The textbook is regarded as a great introductory resource while needing supplementary materials for more advanced learning. **
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ventajas
- Comprehensive coverage of foundational topics in data science.
- Structured guidance for beginners, making complex topics more approachable.
- Encourages logical thinking and problem-solving abilities.
- Initial practical programming exposure through real tasks.
Contras
- Lacks detailed explanations on critical techniques like Random Forest and Gradient Boosting.
Product Price History
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características y beneficios
- Learn data analysis hands-on with Python through a structured approach.
- Based on a popular University of Tokyo course with over 1,800 applications.
- Focuses on essential skills in Python, statistics, and machine learning.
- Includes practical exercises for real-world data analysis.
- Targeted at university students and working adults with programming experience.
- Aims to take readers from introductory to intermediate levels of data science.
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