원본 보기
0 ratings
Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning
genuine image
Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning
Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning
Master linear algebra, calculus, and probability theory for ML.
Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning
제품번호 #: 139778066

Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning

제품번호 #: 139778066

KRW 105517

KRW 122755

Price Details

Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )

*All items will import from 미국

14%

0 ratings 리뷰 작성
재고
미국 USA 스토어에서 가져옴

QTY:

지금 주문하시면 도착 예정일 화요일, 7월 28
Secured transactionsecured transaction

Ubuy works hard to protect your security and privacy. Our advanced payment security system ensures confidentiality by encrypting your information during transmission using AES (Advanced Encryption Standards) and SSL (Secure Socket Layer) protocols. Your payment details are 100% secure as we do not share your payment details with third party sellers.

Our Top Logistics Partners
  • fedex
  • dhl
Master linear algebra, calculus, and probability theory for ML.
자세히 표시
U-Care 보증:
없음
요금제 선택
fast shipping

Fast
Shipping

free return

Free
Return*

secure packaging

Secure Packaging

100% original products

100% Original Products

pci-dss

PCI DSS Compliance

iso certified

ISO 27001 Certified

paypal payment
visa payment
mastercard payment
bank transfer payment
l. pay payment
culture voucher payment
cashbee payment
toss pay payment
kakao pay payment
lg pay payment
samsung pay payment
credit cards korea payment
happy money payment
teencash payment
t-money payment
book gift voucher payment
egg money payment
mobiamo payment
payco payment
Note: Step Down Voltage Transformer required for using electronics products of 미국 store (110-120). Recommended power converters 지금 구매.

What Stands Out

Comprehensive Curriculum
Covers essential topics like linear algebra, calculus, and probability specifically for machine learning applications, ensuring students acquire foundational skills vital for advanced studies and practical implementations.
Practical Applications
Focuses on real-world scenarios where mathematical concepts are applied in machine learning, bridging the gap between theory and practice, thereby enhancing learners' problem-solving abilities.
Expert Guidance
Designed and taught by industry professionals and academics, offering insights into cutting-edge techniques and methodologies, thus providing learners with valuable mentorship and networking opportunities.

제품 세부 정보

Shop Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning online at a best price in South Korea. 1837027870
  • Build a solid foundation in the core math behind machine learning algorithms with this comprehensive guide to linear algebra, calculus, and probability, explained through practical Python examplesPurchase of the print or Kindle book includes a free PDF eBook Key FeaturesMaster linear algebra, calculus, and probability theory for MLBridge the gap between theory and real-world applicationsLearn Python implementations of core mathematical conceptsBook DescriptionMathematics of Machine Learning provides a rigorous yet accessible introduction to the mathematical underpinnings of machine learning, designed for engineers, developers, and data scientists ready to elevate their technical expertise. With this book, you’ll explore the core disciplines of linear algebra, calculus, and probability theory essential for mastering advanced machine learning concepts. PhD mathematician turned ML engineer Tivadar Danka—known for his intuitive teaching style that has attracted 100k+ followers—guides you through complex concepts with clarity, providing the structured guidance you need to deepen your theoretical knowledge and enhance your ability to solve complex machine learning problems. Balancing theory with application, this book offers clear explanations of mathematical constructs and their direct relevance to machine learning tasks. Through practical Python examples, you’ll learn to implement and use these ideas in real-world scenarios, such as training machine learning models with gradient descent or working with vectors, matrices, and tensors. By the end of this book, you’ll have gained the confidence to engage with advanced machine learning literature and tailor algorithms to meet specific project requirements. What you will learnUnderstand core concepts of linear algebra, including matrices, eigenvalues, and decompositionsGrasp fundamental principles of calculus, including differentiation and integrationExplore advanced topics in multivariable calculus for optimization in high dimensionsMaster essential probability concepts like distributions, Bayes' theorem, and entropyBring mathematical ideas to life through Python-based implementationsWho this book is forThis book is for aspiring machine learning engineers, data scientists, software developers, and researchers who want to gain a deeper understanding of the mathematics that drives machine learning. A foundational understanding of algebra and Python, and basic familiarity with machine learning tools are recommended. Table of ContentsVectors and vector spacesThe geometric structure of vector spacesLinear algebra in practice spaces: measuring distancesLinear transformationsMatrices and equationsEigenvalues and eigenvectorsMatrix factorizationsMatrices and graphsFunctionsNumbers, sequences, and seriesTopology, limits, and continuityDifferentiationOptimizationIntegrationMultivariable functionsDerivatives and gradientsOptimization in multiple variablesWhat is probability?Random variables and distributionsThe expected valueThe maximum likelihood estimationIt's just logicThe structure of mathematicsBasics of set theoryComplex numbers
Publisher Packt Publishing
Publication date May 30, 2025
Language English
Print length 730 pages
ISBN-10 1837027870
ISBN-13 978-1837027873
Item Weight 2.72 pounds (1.23 kg)
Dimensions 7.5 x 1.65 x 9.25 inches (19.1 x 4.2 x 23.5 cm)

Who Should Buy?

Suitable For
  • Aspiring Data Scientists

    Ideal for those starting a career in data science seeking foundational knowledge in mathematical concepts for machine learning.

  • Undergraduate Students

    University students pursuing courses in mathematics, statistics, or computer science will find this material enhances their understanding.

  • Machine Learning Enthusiasts

    Individuals interested in deepening their knowledge of machine learning frameworks and algorithms through mathematical principles will benefit.

Not Suitable For
  • Beginners Without Background

    Complete beginners with no mathematical foundation may struggle and find the concepts too advanced or overwhelming.

제품 설명

질문이 있으십니까? 채팅하기

고객 질문 및 답변

  • 의문: What topics are covered in the Mathematics of Machine Learning book?

    답변: The book covers essential topics including linear algebra, calculus, and probability, which are fundamental for understanding machine learning algorithms. These subjects help build a strong mathematical foundation necessary for grasping complex machine learning concepts. For instance, linear algebra is critical for understanding data structures in machine learning, while calculus is important for optimization techniques. This foundational knowledge enables readers to effectively develop, implement, and troubleshoot machine learning models.
  • 의문: Who is the target audience for this book?

    답변: This book is designed for students, professionals, and anyone interested in mastering the mathematical concepts behind machine learning. It's ideal for those who already have a basic understanding of mathematics and are looking to deepen their knowledge for practical applications in data science and machine learning projects. By tackling real-world problems and examples, readers can effectively apply mathematical theories to various machine learning scenarios in industries such as finance, healthcare, and technology.
  • 의문: How can mastering mathematics improve my machine learning skills?

    답변: Mastering mathematics enhances your ability to understand and implement machine learning algorithms more effectively. A strong grasp of linear algebra allows you to manipulate data structures, while calculus helps you optimize models through techniques like gradient descent. Probability enables you to assess model accuracy and uncertainty. This knowledge not only aids in better model performance but also allows you to critically evaluate and troubleshoot existing algorithms in real-world applications.
  • 의문: Is prior knowledge of mathematics required to read this book?

    답변: While prior exposure to basic mathematical concepts is beneficial, the book provides thorough explanations to accommodate readers with varying levels of expertise. It gradually introduces more complex topics, ensuring that even those with limited backgrounds in mathematics can grasp the essential ideas. This structured approach allows readers to build confidence and gradually tackle more intricate topics relevant to machine learning, making it accessible for self-learners and students alike.
  • 의문: What practical applications does knowledge from this book enable?

    답변: Knowledge from this book equips you for various applications in fields such as data analysis, artificial intelligence, and predictive modeling. By mastering the underlying mathematical principles, you can design machine learning algorithms, build predictive models, or analyze large datasets effectively. Whether working on a personal project, contributing to a research initiative, or pursuing a career in data science, the skills gained from this book can significantly enhance your ability to solve real-world problems powered by machine learning.
  • 의문: Can this book help with preparing for machine learning interviews?

    답변: Absolutely! This book is an excellent resource for honing the mathematical skills often assessed in machine learning job interviews. By thoroughly understanding linear algebra, calculus, and probability, you can confidently answer technical questions and tackle case studies related to algorithm design and data interpretation. The comprehensive coverage of mathematical concepts ensures you are well-prepared to demonstrate your analytical capabilities in interviews, making you a strong candidate in the competitive job market of data science.
  • 의문: How does this book compare to other machine learning resources?

    답변: This book stands out by focusing specifically on the mathematical foundations of machine learning, rather than solely on programming or application tools. Many resources may emphasize case studies or software implementation, while this one prioritizes the underlying mathematics, allowing for a deep understanding of how algorithms function. This unique emphasis prepares readers not just to use machine learning tools, but to innovate and troubleshoot, making it an excellent companion to more application-focused texts.
  • 의문: Are there exercises or practical examples included in the book?

    답변: Yes, the book includes various exercises and practical examples to reinforce the mathematical concepts covered. These examples not only illustrate the theoretical points but also encourage readers to apply what they have learned to real-world problems. Engaging with these exercises helps to solidify understanding and creates a pathway for learners to connect theory with practice, which is crucial in mastering the application of mathematics in machine learning.
  • 의문: Where can I buy Mathematics of Machine Learning: Master linear algebra, calculus, and probability for machine learning in South Korea?

    답변: You can purchase the Mathematics of Machine Learning from Ubuy in South Korea. Ubuy offers a wide range of books, including those focused on mathematics and machine learning. Shopping through Ubuy provides you with a convenient platform to explore various editions, compare options, and find related products to enhance your knowledge in machine learning.
  • 의문: What skills can I expect to gain after reading this book?

    답변: After reading this book, you can expect to gain a strong foundation in mathematics that enhances your analytical skills. You’ll learn how to manipulate and analyze data using linear algebra, apply calculus to optimize machine learning models, and understand the principles of probability that underpin data-driven decisions. These skills are vital in various applications, enabling you to tackle complex problems and innovate within the field of machine learning confidently.

Study & Teaching Editorial Review

  • ubuy South Korea
  • ubuy South Korea
  • ubuy South Korea
  • ubuy South Korea
  • ubuy South Korea
  • ubuy South Korea
  • ubuy South Korea
  • ubuy South Korea
  • ubuy South Korea
편집 리뷰가 없습니다.

Customer Reviews & Ratings

4.3
108 고객 평가
  • 5 점
    70%
  • 4 점
    13%
  • 3 점
    8%
  • 2 점
    2%
  • 1 점
    7%

이 제품 리뷰하기

다른 고객들과 의견을 공유하세요.

Platform Trust & Buyer Confidence

trustpilot logo
4.3/5 9,000 + reviews
Read reviews
MT
Mohd
Verified buyer

“The product received very good packaging & safe…Thank You”

16 June 2026 · via Trustpilot
SJ
Shawati
Verified buyer

“Accurate delivery timing given”

16 June 2026 · via Trustpilot
YB
Youcef
Verified buyer

“Not madly expensive like I thought, and much quicker than promised.”

15 June 2026 · via Trustpilot
LM
Leila
Verified buyer

“Never dealt with Ubuy before, but everything worked out great. Seamless cross border purchasing and shipping. Thanks!”

6/7/2026 · via Trustpilot
KA
Kwame
Verified buyer

“The process was smooth, with clear communication and timelines. This was my 1st purchase and I am really impressed. I will definitely be coming back.”

12 June 2026 · via Trustpilot
보안 결제 Global Delivery Easy Returns Genuine Products

Product Price History

중요 정보

  • 제한 사항: 국제 배송되는 제품의 경우 제조업체 보증이 유효하지 않을 수 있으며, 제조업체 서비스 옵션을 사용하지 못하거나 제품 설명서, 지침 및 안전 경고가 대상 국가 언어로 표시되지 않을 수 있으며, 제품(및 첨부 자료)은 도착 국가 표준, 사양 및 라벨링 요구 사항에 따라 설계되지 않을 수 있으며, 제품은 목적지 국가 전압 및 기타 전기 표준을 준수하지 않을 수 있습니다(가능한 경우 어댑터 또는 변환기 사용 필요). 수령인은 제품을 도착 국가로 합법적으로 수입할 수 있는지 확인할 책임이 있습니다. Ubuy 또는 그 제휴사에서 주문할 때, 수령인은 기록 수입자로서 도착 국가의 모든 법률과 규정을 준수해야 합니다.
  • Ubuy는 글로벌 검색 엔진이므로 Ubuy에 나열된 모든 제품이 판매용은 아닙니다. 제품은 수출/무역 규정을 따릅니다.

KRW 105517

KRW 122755

지금 주문하시면 도착 예정일 화요일, 7월 28

QTY:

Secured transactionsecured transaction

PCI DSS compliant and ISO 27001:2022 certified, with encrypted payments and full buyer protection on every order.

Our Top Logistics Partners
  • fedex
  • dhl
Fastest cross-border delivery

특징 및 장점

  • Comprehensive guide to the mathematics behind machine learning.
  • Covers linear algebra, calculus, and probability with practical Python examples.
  • Written by PhD mathematician and ML engineer Tivadar Danka.
  • Ideal for engineers, developers, and data scientists looking to enhance their expertise.
  • Balances theory with real-world applications in machine learning.
  • Includes a free PDF eBook with the purchase of print or Kindle version.

Ubuy Assurance

Experience worry-free shopping with 100% original products, PCI DSS-compliant payment security, ISO 27001-certified data protection, the fastest cross-border delivery, free returns *, and secure packaging on every order.