Interpretable Machine Learning with Python: Build explainable, fair, and robust high-performance models with hands-on, real-world examples
genuine image
Interpretable Machine Learning with Python: Build explainable, fair, and robust high-performance models with hands-on, real-world examples
A deep dive into the key aspects and challenges of machine learning interpretability using a comprehensive toolkit to build fairer, safer, and more reliable models.
Interpretable Machine Learning with Python: Build explainable, fair, and robust high-performance models with hands-on, real-world examples
منتج #: 84924443

Interpretable Machine Learning with Python: Build explainable, fair, and robust high-performance models with hands-on, real-world examples

88% من المشترين سيوصون بهذا المنتج لصديق

منتج #: 84924443

TND 125

تفاصيل السعر

باستثناء رسوم الشحن والجمارك ( سيتم احتساب رسوم الشحن والجمارك عند إتمام الشراء )

*سيتم استيراد جميع العناصر من أمريكا

متوفر فى المخزون
أمريكا مستورد من متجر USA

كمية:

اطلب الآن واحصل عليه حول السبت, أكتوبر 10
معاملة آمنةمعاملة آمنة

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

أفضل شركائنا اللوجستيين
  • fedex
  • dhl
A deep dive into the key aspects and challenges of machine learning interpretability using a comprehensive toolkit to build fairer, safer, and more reliable models.
كفالة يو كير:
لا شيء
اختر الباقة
fast shipping

شحن
سريع

free return

استرجاع
مجاني*

تغليف آمن

تغليف آمن

منتجات أصلية %100

منتجات أصلية %100

pci-dss

الامتثال لمعيار PCI DSS

iso certified

حاصل على شهادة ISO 27001

paypal payment
visa payment
mastercard payment
Note: Step Down Voltage Transformer required for using electronics products of أمريكا store (110-120). Recommended power converters اشتري الآن.

أبرز ما يلفت الانتباه

Hands-On Learning
The book provides practical, real-world examples, allowing readers to engage directly with interpretable machine learning concepts, making complex ideas more accessible and understandable.
Focus on Fairness
Addresses critical issues of fairness in machine learning, guiding readers on techniques to ensure that their models are both explainable and equitable, which enhances trustworthiness in automated decisions.
Robust Performance
Equips users with strategies to build high-performance models that maintain robustness across different datasets, ensuring reliability and effectiveness in diverse applications of machine learning.

تفاصيل المنتج

Shop Interpretable Machine Learning with Python: Build explainable, fair, and robust high-performance models with hands-on, real-world examples online at a best price in Tunisia. 180323542X
Publisher Packt Publishing
Publication date October 31, 2023
Edition 2nd ed.
Language English
Print length 606 pages
ISBN-10 180323542X
ISBN-13 978-1803235424
Item Weight 2.26 pounds (1.03 kg)
Dimensions 7.5 x 1.37 x 9.25 inches (19.1 x 3.5 x 23.5 cm)

من يجب أن يشتري؟

Suitable For
  • Data Scientists

    Ideal for data scientists seeking to enhance the interpretability and fairness of their machine learning models.

  • AI Researchers

    Perfect resource for AI researchers focused on developing explainable algorithms and understanding model behavior in real-world applications.

  • Educators

    Suitable for educators teaching machine learning concepts, emphasizing practical, hands-on learning with interpretable models.

Not Suitable For
  • Beginners

    Not suitable for absolute beginners without prior knowledge of machine learning concepts and Python programming.

وصف المنتج

Interpretable Machine Learning with Python: Build explainable, fair, and robust high-performance models with hands-on, real-world examples

هل لديك أي استفسار؟ تحدث معنا

أسئلة العملاء & الإجابات

  • سؤال: What is the main focus of 'Interpretable Machine Learning with Python'?

    إجابه: The primary focus of 'Interpretable Machine Learning with Python' is to provide readers with the tools and techniques to create machine learning models that are not only effective but also interpretable. The book emphasizes the importance of understanding model behavior, especially in critical areas like healthcare or finance, where decisions significantly impact lives. By incorporating hands-on real-world examples, it showcases practical applications, enabling readers to grasp complex concepts and apply them to their own projects, making it essential for both practitioners and students.
  • سؤال: Who should read 'Interpretable Machine Learning with Python'?

    إجابه: 'Interpretable Machine Learning with Python' is ideal for data scientists, machine learning practitioners, and students who wish to deepen their understanding of explainable AI. It is also suitable for professionals in sectors where transparency in machine learning decisions is crucial, such as finance, healthcare, and technology. The book is written in an accessible manner, making complex concepts understandable for beginners while providing advanced insights for seasoned practitioners, thus catering to a wide audience with varying levels of expertise.
  • سؤال: What type of machine learning models are covered in the book?

    إجابه: The book covers a diverse array of machine learning models, including both traditional techniques like decision trees and linear regression, as well as more complex models such as ensemble methods and neural networks. Each model is explored with a focus on interpretability, providing tools and methodologies to analyze and explain outputs effectively. By examining various model types, readers can learn how to select the appropriate model based on their specific data and business needs, applying best practices in diverse domains.
  • سؤال: How does the book address fairness in machine learning?

    إجابه: The book addresses fairness in machine learning by discussing bias in algorithms and the ethical implications of deploying machine learning models in real-world scenarios. It explains frameworks for assessing and mitigating bias, ensuring that models serve all demographics equitably. Readers will learn about techniques to evaluate fairness metrics in their models, fostering an understanding that responsible AI requires not just accuracy but also fairness, ultimately leading to models that are both effective and socially responsible.
  • سؤال: What practical examples are included in the book?

    إجابه: The book includes a variety of practical, real-world examples that illustrate the application of interpretable machine learning principles. These examples range across different industries, such as predicting loan defaults in finance or diagnosing diseases in healthcare. Such hands-on projects help readers apply the concepts learned in a tangible way, reinforcing their understanding and boosting their confidence in implementing similar projects in their work or studies. The examples also demonstrate how to leverage the models for impactful decision-making, making the content relatable and applicable.
  • سؤال: What tools and libraries are recommended in the book?

    إجابه: The book recommends using popular Python libraries such as scikit-learn, pandas, and matplotlib for implementing interpretable machine learning models. It also discusses specialized libraries like SHAP (SHapley Additive exPlanations) and LIME (Local Interpretable Model-agnostic Explanations) that are specifically designed for model interpretation. By encouraging the use of these tools, the book facilitates readers’ ability to create and communicate their models effectively, as these libraries provide powerful functionalities for analysis and visualization, enhancing their machine learning practice.
  • سؤال: Can I learn about advanced techniques in machine learning from this book?

    إجابه: 'Interpretable Machine Learning with Python' provides insights into advanced machine learning techniques while maintaining a focus on interpretability. Readers will be introduced to sophisticated concepts such as feature importance, model-agnostic interpretations, and post-hoc explanations. Each advanced technique is presented with clarity, enabling readers to understand when and how to implement these methods in their own projects. These insights are particularly useful for practitioners who wish to elevate their machine learning skills without sacrificing model transparency.
  • سؤال: How can I implement the concepts learned from this book in my projects?

    إجابه: To implement the concepts learned from 'Interpretable Machine Learning with Python' in your projects, start by identifying a specific problem you aim to solve using machine learning. Apply the book's techniques in data preprocessing, model selection, and evaluation to build your model while keeping interpretability in mind. Utilize the provided examples as a template for your projects, tweaking them to fit your data and objectives. This hands-on application not only solidifies your understanding but also helps in developing robust and explainable models that can be trusted in decision-making.
  • سؤال: What is new in the 2nd edition of the book?

    إجابه: The 2nd edition of 'Interpretable Machine Learning with Python' features updated content that reflects the latest advancements in the field of machine learning and AI interpretability. New chapters have been added that discuss recent frameworks, tools, and methodologies, thus providing readers with an up-to-date perspective. Additionally, the practical examples have been refreshed to include more current case studies and applications, enriching the learning experience and ensuring that readers are learning relevant and practical skills applicable in today’s data-driven world.
  • سؤال: Where can I buy 'Interpretable Machine Learning with Python' in Tunisia?

    إجابه: You can buy 'Interpretable Machine Learning with Python' from Ubuy in Tunisia. Ubuy offers a convenient way to access this essential resource through their online platform, ensuring you have the latest edition available for your learning and professional development. Whether you are a student or a seasoned professional, Ubuy provides a reliable and straightforward purchasing experience to get your hands on this valuable book.

Expert Systems Editorial Review

**** "Interpretable Machine Learning with Python - Second Edition," authored by Serg Masís and published by Packt, has garnered widespread acclaim for its comprehensive and practical approach to demystifying the complexities of machine learning model interpretation. The structure of the book, built around distinct "missions," enhances the reader's engagement by combining theoretical concepts with hands-on Python code and illustrative plots. Such an approach is particularly beneficial for both beginners and advanced practitioners, making the content accessible while also offering depth. One of the book’s key strengths lies in its emphasis on explainability, interpretability, and their implications for fairness and reliability in machine learning. Readers are introduced to essential terminologies and different model types, including black-box, white-box, and glass-box models. Practical applications, such as the exploration of bias in datasets, further emphasize the importance of understanding machine learning outcomes in real-world scenarios. The author masterfully bridges theory with application, illustrating how shortcomings in model interpretability can manifest in critical real-life decision-making processes. The breadth of topics covered, ranging from traditional methods of interpretation to complex architectures like convolutional neural networks and natural language processing, ensures that the book remains relevant in the fast-evolving landscape of machine learning. The included case studies and additional resources, such as the active Discord community, enhance learning by fostering collaboration and discussion among readers. This book not only serves as a foundational resource but also challenges practitioners to actively engage with interpretable machine learning tools, reinforcing the notion that understanding the "why" behind model decisions is paramount. With its combination of detailed explanations, practical examples, and strategic guidance on avoiding pitfalls, "Interpretable Machine Learning with Python" stands out as an essential read for anyone looking to grasp the intricacies of machine learning interpretation. **

مراجعات العملاء وتقييماتهم

1 تقييمات العملاء
  • 5 نجمة
    0%
  • 4 نجمة
    100%
  • 3 نجمة
    0%
  • 2 نجمة
    0%
  • 1 نجمة
    0%

أضف تقييم لهذا المنتج

شارك أفكارك مع عملاء آخرين

إيجابيات

  • Structured approach with clear "missions" enhancing engagement.
  • Comprehensive coverage of key interpretability concepts and tools.
  • Practical applications with real-world case studies.
  • Suitable for beginners and advanced readers alike.
  • Active support community via Discord.
  • Offers valuable insights into advanced topics like CNNs and NLP.

سلبيات

  • Lengthy due to its ambitious scope, which may overwhelm some readers.

منصة موثوقة وثقة كاملة للمشتري

trustpilot logo
4.2/5 9477 التقييمات
اطّلع على التقييمات
JK
Jasmin
مشتري موثّق

“Great products and very good service: very easy and very fast international delivery.”

9 September 2026 · عبر Trustpilot
AG
Anke
مشتري موثّق

“Wonderful online shopping experience, smooth transaction from the start. Payment method works conveniently and delivery is unexpectedly fast and reliable. You go the extra mile for service. What makes this even more amazing, you deliver to Namibia. I will remain a happy Ubuy customer and will increase my purchases for sure! Thank you!”

10 September 2026 · عبر Trustpilot
H
Hazel
مشتري موثّق

“Very easy to find the products what you need, and so fast delivery, that’s why I highly recommended to others costumers to used ubuy.”

10 September 2026 · عبر Trustpilot
O
Opaleye
مشتري موثّق

“I received exactly what I ordered I was skeptical about your site because that was my first time to order. But the order came timely and neatly packaged. I was not disappointed. Thank you.”

11 September 2026 · عبر Trustpilot
AC
Adele
مشتري موثّق

“Easy to find and order what you want on the website. Delivery is quick to the UK”

8 September 2026 · عبر Trustpilot
الخروج الآمن شحن عالمي إسترجاع سهل منتجات أصلية

تاريخ سعر المنتج

معلومات مهمة

  • القيود: بالنسبة للمنتجات التي يتم شحنها دولياً، يُرجى ملاحظة أن أي ضمان من الشركة المصنعة قد لا يكون صالحاً؛ قد لا تتوفر خيارات خدمة الشركة المصنعة؛ قد لا تكون أدلة المنتج والتعليمات وتحذيرات السلامة مكتوبة بلغة بلد المقصد؛ قد لا يتم تصميم المنتجات (والمواد المصاحبة لها) وفقاً لمعايير بلد الوجهة والمواصفات ومتطلبات الملصقات؛ وقد لا تتوافق المنتجات مع الجهد الكهربي المستخدم في بلد الوجهة والمعايير الكهربائية الأخرى (تتطلب استخدام محوّل كهربي أو جهاز تحويل إذا كان ذلك مناسباً). المستلم مسؤول عن ضمان إمكانية استيراد المنتج بشكل قانوني إلى بلد الوجهة. عند الطلب من يوباي أو الشركات التابعة لها، يكون المستلم هو المستورد المسجل ويجب أن يلتزم بجميع القوانين واللوائح الخاصة ببلد الوجهة.
  • ليست كل المنتجات المدرجة على يوباي معروضة للبيع، لأن يوباي هو محرك بحث عالمي. المنتجات تخضع للوائح التصدير / التجارة.

TND 125

اطلب الآن واحصل عليه حول السبت, أكتوبر 10

كمية:

معاملة آمنةمعاملة آمنة

نوفر لك مدفوعات مشفّرة، وحماية متكاملة للمشتري، مع الالتزام بمعايير PCI DSS وشهادة ISO 27001:2022 لضمان أعلى مستويات الأمان في كل عملية شراء.

أفضل شركائنا اللوجستيين
  • fedex
  • dhl
أسرع توصيل عبر الحدود

المميزات والفوائد

  • Helps make machine learning models more robust, transparent, and fair
  • Covers interpretability methods for white-box and black-box models
  • Provides specific methods for deep learning models in vision, text, and time series domains
  • Offers advice for companies using black-box models to prioritize transparency
  • Focuses on explaining model decisions to uncover and mitigate biases
  • Includes key features like SHAP, feature importance, and causal inference

ضمان Ubuy

تسوّق بثقة مع منتجات أصلية %100، ومدفوعات آمنة متوافقة مع معيار PCI DSS، وحماية بيانات معتمدة وفق ISO 27001، وشحن دولي سريع، وإرجاع مجاني*، وتغليف آمن لكل طلب.