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Machine Learning Algorithms: Handbook
Machine Learning Algorithms: Handbook
Packed with practical examples using Python and code snippets, you'll gain a hands-on understanding of how each algorithm works and learn to implement them in real projects.
Machine Learning Algorithms: Handbook
Artikal br.: 80060774

Machine Learning Algorithms: Handbook

Artikal br.: 80060774

BAM 113

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Packed with practical examples using Python and code snippets, you'll gain a hands-on understanding of how each algorithm works and learn to implement them in real projects.
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What Stands Out

Comprehensive Coverage
This handbook offers an extensive overview of various machine learning algorithms, making it a vital resource for both beginners and experts seeking to deepen their understanding of the subject.
Latest Insights
Published in September 2023, the content is up-to-date with the latest developments in machine learning, ensuring readers are informed about current trends and practices in the field.
Practical Applications
The book includes real-world examples and practical applications of machine learning algorithms, helping readers to apply theoretical concepts effectively in their projects and endeavors.

Detalji o proizvodu

Shop Machine Learning Algorithms: Handbook online at a best price in Bosnia and Herzegovina. 935648483X
  • In Machine Learning Algorithms: Handbook, Aman Kharwal, founder of Statso.io, takes you on an enlightening journey through the fascinating world of machine learning. Whether you are a seasoned data scientist or a curious beginner, this book provides a holistic overview of the essential algorithms that form the backbone of modern machine learning.With clarity and precision, Aman demystifies complex concepts, guiding you step-by-step through the fundamentals of regression, classification, clustering, deep learning, and time series forecasting. Each chapter presents a deep dive into a specific algorithm, equipping you with the knowledge and skills to tackle real-world problems head-on.Key Features: 1. Clear Explanations of Machine Learning Algorithms: The book offers clear and concise explanations of machine learning algorithms, ensuring that readers of all levels can grasp the concepts effortlessly.2. Hands-On Approach: Packed with practical examples using Python and code snippets, you'll gain a hands-on understanding of how each algorithm works and learn to implement them in real projects.3. Comprehensive Coverage: From linear regression and support vector machines to decision trees and neural networks, the book covers a wide array of algorithms, giving you a solid foundation to explore diverse problem domains.4. Performance Evaluation Methods: Learn how to evaluate the effectiveness of your models, identify areas for improvement, and optimize their performance using industry-standard evaluation techniques.5. Data Preprocessing Techniques: Discover the critical elements of data preprocessing that lay the groundwork for building robust and accurate machine learning models.6. Time Series Forecasting: Explore advanced algorithms specifically designed for time series data, a critical component of numerous real-world applications.7. Appendix for Easy Reference: Access all parameters of commonly used machine learning algorithms in a handy appendix, facilitating efficient model tuning.Whether you are interested in learning the fundamentals of all Machine Learning algorithms, implementation of Machine Learning algorithms using Python, or preparing for an interview, Machine Learning Algorithms: Handbook will help you in every way.
Publisher Clever Fox Publishing
Publication date September 9, 2023
Language English
Print length 234 pages
ISBN-10 935648483X
ISBN-13 978-9356484832
Dimensions 6 x 0.61 x 9 inches (15.2 x 1.5 x 22.9 cm)
Package Weight1 Pound

Who Should Buy?

Suitable For
  • Beginners in ML

    Ideal for those new to machine learning, providing foundational knowledge and easy-to-understand algorithms.

  • Data Science Students

    Perfect for students pursuing data science, offering practical examples and a solid understanding of various algorithms.

  • Self-Learners

    Suitable for individuals interested in self-learning machine learning concepts and applications through a structured handbook.

Not Suitable For
  • Advanced ML Experts

    Not suitable for seasoned machine learning professionals seeking in-depth, cutting-edge research or advanced topics.

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Pitanja i odgovori kupaca

  • Pitanje: Kako kupovati Machine Learning Algorithms: Handbook online od Ubuya?

    Odgovor: Lako je kupovati Machine Learning Algorithms: Handbook online od Ubuya.. Vi samo trebate potražiti proizvod, odabrati način dostave prilikom odjavljivanja i dostaviti ga na vašu lokaciju.
  • Pitanje: Je li Machine Learning Algorithms: Handbook dostupan za online kupovinu u Bosnia and Herzegovina?

    Odgovor: Da, u Ubuy Bosnia and Herzegovina ovaj proizvod je dostupan za kupovinu po razumnoj cijeni.. Machine Learning Algorithms: Handbook nije dostupan lokalno, ali možete nam povjeriti naše usluge ekspresne dostave.
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Intelligence & Semantics Editorial Review

The "Machine Learning Algorithms: Handbook" is receiving positive feedback from customers. Readers appreciate the clear and easy-to-understand explanations of machine learning algorithms, along with the accompanying code implementations. The inclusion of bonus chapters on neural networks and a comprehensive explanation of important hyperparameters for all algorithms is also well-received. Reviewers note that the book is great for beginners, providing a simple and concise handbook for those looking to gain a clear understanding of machine learning concepts. Despite the higher price, readers feel that the usage and print quality justify the cost. Additionally, followers of the author's projects find the book to be exceptional and are looking forward to more similar publications in the future.

Customer Reviews & Ratings

4.2
31 ocjene korisnika
  • 5 zvijezda
    55%
  • 4 zvijezda
    29%
  • 3 zvijezda
    8%
  • 2 zvijezda
    4%
  • 1 zvijezda
    4%

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Pros

  • Clear and easy-to-understand explanations
  • In-depth code implementations
  • Bonus chapters on neural networks
  • Comprehensive explanation of important hyperparameters
  • Great for beginners

Cons

  • Higher price than other similar books

Product Price History

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