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- Practical Machine Learning with R and Python:...
Practical Machine Learning with R and Python: Third Edition: Machine Learning in Stereo
85% من المشترين سيوصون بهذا المنتج لصديق
LYD 136
تفاصيل السعر
باستثناء رسوم الشحن والجمارك ( سيتم احتساب رسوم الشحن والجمارك عند إتمام الشراء )
*سيتم استيراد جميع العناصر من أمريكا
كمية:
تعمل يوباي جاهدة لحماية أمنك وخصوصيتك. يضمن نظام أمان الدفع المتقدم لدينا السرية من خلال تشفير معلوماتك أثناء النقل باستخدام بروتوكولات AES (معايير التشفير المتقدمة) وSSL (طبقة المنافذ الآمنة). تفاصيل الدفع الخاصة بك آمنة بنسبة %100 لأننا لا نشارك تفاصيل الدفع الخاصة بك مع بائعين تابعين لجهات خارجية
This book should serve as a useful and handy reference for Machine Learning algorithms in both R and Python.
شحن
سريع
استرجاع
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تفاصيل المنتج
| Publisher | Independently published |
| Publication date | January 1, 2019 |
| Language | English |
| Print length | 276 pages |
| ISBN-10 | 1792969309 |
| ISBN-13 | 978-1792969300 |
| Item Weight | 1.1 pounds (500 grams) |
| Dimensions | 7.44 x 0.63 x 9.69 inches (18.9 x 1.6 x 24.6 cm) |
من يجب أن يشتري؟
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Beginner Data Scientists
Ideal for newcomers to machine learning, providing foundational knowledge using both R and Python programming.
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Academic Students
Great for students in data science courses who need practical examples and exercises in their curriculum.
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Practical Analysts
Suitable for analysts looking to implement machine learning models in real-world applications using popular programming languages.
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Advanced Practitioners
Experienced data scientists may find the content too basic and not sufficiently challenging or advanced.
وصف المنتج
Practical Machine Learning with R and Python: Third Edition: Machine Learning in Stereo
أسئلة العملاء & الإجابات
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سؤال:
What is the focus of 'Practical Machine Learning With R And Python: Third Edition'?
إجابه: This book focuses on providing a comprehensive understanding of machine learning using R and Python together. It covers essential concepts, techniques, and real-world applications, making it suitable for both beginners and advanced users. By utilizing both programming languages, readers gain insights into various machine learning algorithms, data processing techniques, and practical implementation strategies. Practical use cases include predictive analytics in business, natural language processing for text analysis, and image classification projects. -
سؤال:
Who is the target audience for this book?
إجابه: The target audience for this book includes data scientists, machine learning practitioners, and students interested in enhancing their skills in machine learning. It’s suitable for readers who are familiar with the basics of programming and statistical analysis, allowing them to transition into more advanced topics seamlessly. The book also serves as a valuable reference for professionals looking to implement machine learning techniques in their work across various industries, including finance, healthcare, and technology. -
سؤال:
What programming skills are required to understand the content of this book?
إجابه: A basic understanding of programming in R and Python is recommended to get the most out of this book. Familiarity with data manipulation, basic statistics, and machine learning concepts will greatly enhance your learning experience. The book provides clear explanations and examples, so even if you're not an expert, you can gradually build your skills. This approach is useful for applying machine learning in various scenarios, such as developing recommendation systems or conducting data-driven research. -
سؤال:
What kind of practical examples does the book provide?
إجابه: The book offers multiple practical examples that demonstrate the application of various machine learning algorithms using R and Python. Examples include creating predictive models for sales forecasting, employing clustering methods to segment customers, and using decision trees for classification tasks. Each example is designed to be relatable, providing context that readers can apply directly to their own projects, thus bridging theory and practice. -
سؤال:
How does this edition differ from previous editions?
إجابه: The third edition of 'Practical Machine Learning With R And Python' has been updated to include the latest advancements in the field of machine learning and incorporates new libraries and frameworks. It also provides enhanced examples and case studies relevant to contemporary issues, making it more applicable to today's data science challenges. The inclusion of updated tools helps practitioners stay current with the rapidly evolving machine learning landscape, making it an essential resource. -
سؤال:
Are there prerequisites to keep in mind before reading this book?
إجابه: While there are no formal prerequisites, readers are encouraged to have a foundational knowledge of programming concepts and basic statistics. Familiarity with data manipulation and analysis will greatly benefit those looking to dive into machine learning with R and Python. For those who are complete beginners, it might be helpful to take introductory courses or tutorials in both programming languages prior to beginning the book, ensuring a smoother learning experience. -
سؤال:
What types of projects can I implement after learning from this book?
إجابه: After studying the content in this book, you can implement various projects such as developing a movie recommendation system, predicting customer churn in subscription services, or analyzing social media sentiment. The skills acquired allow you to tackle real-world data science problems across disciplines, enabling innovative solutions that can help organizations make data-informed decisions. This practical approach is essential for anyone looking to apply machine learning techniques effectively. -
سؤال:
Is this book suitable for advanced machine learning practitioners?
إجابه: Yes, this book caters not only to beginners but also to advanced machine learning practitioners. It delves into complex topics and advanced techniques, offering insights into performance optimization and model evaluation. For seasoned data scientists, it serves as a valuable reference for frameworks and hands-on implementations that may not be covered extensively in typical coursework. This broadens their toolkit and fosters new ideas for advanced projects or research. -
سؤال:
What resources does the book recommend for further learning?
إجابه: The book provides a variety of resources for further learning, including online courses, tutorials, and specific library documentation for R and Python. It also suggests various datasets for practical experimentation, enabling continued practice and exploration beyond the book's exercises. Engaging with these additional resources can significantly enhance your understanding and skills in machine learning, supporting your development as a proficient data scientist. -
سؤال:
Where can I buy 'Practical Machine Learning With R And Python: Third Edition' in Libya?
إجابه: You can buy 'Practical Machine Learning With R And Python: Third Edition' at Ubuy. Ubuy offers a wide selection of books and provides international shipping options. Their user-friendly interface makes it easy to find and purchase this title, ensuring you can get your hands on it quickly and efficiently, giving you the tools to dive into machine learning.
Algorithms Editorial Review
مراجعات العملاء وتقييماتهم
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معلومات مهمة
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كمية:
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المميزات والفوائد
- Third edition offers updated content and code.
- Covers a wide range of Machine Learning algorithms.
- Provides R and Python implementations side-by-side.
- Includes essential programming concepts for beginners.
- Serves as a handy reference for both novices and experts.
- Focuses on practical applications with detailed examples.
ضمان Ubuy
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