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Vare #:
112607187
Linear Algebra for Data Science, Machine Learning, and Signal Processing Hardcover – 16 May 2024
Vare #:
112607187
DKK 992
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Vores bedste logistikpartnere
Maximise student engagement and understanding of matrix methods in data-driven applications with this modern teaching package.
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Hvad der skiller sig ud
Comprehensive Coverage
Offers a thorough exploration of linear algebra concepts, tailored specifically for applications in data science, machine learning, and signal processing, ensuring a deep understanding for learners.
Practical Applications
Focuses on real-world applications and problem-solving techniques, enabling readers to effectively apply linear algebra techniques in their projects and research across various emerging fields.
Expertly Crafted
Written by industry experts and academics, this resource provides a blend of theory and practice, equipping readers with the high-quality knowledge necessary to excel in modern analytical environments.
Produktdetaljer
| Item Weight | 2 lbs (910 grams) |
Hvem bør købe?
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Data Science Students
Students pursuing data science will benefit from foundational linear algebra skills necessary for data analysis and modeling.
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Machine Learning Practitioners
Practitioners looking to deepen their understanding of machine learning algorithms will find valuable insights in this text.
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Signal Processing Engineers
Engineers working in signal processing will appreciate the practical applications of linear algebra in their field.
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Beginners in Mathematics
Complete novices in mathematics may struggle with the complex concepts presented without prior foundational knowledge.
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Casual Learners
Individuals seeking a light introduction to linear algebra might find this textbook too dense and technical.
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Non-Technical Readers
Readers without a technical background may find the content difficult to understand and apply in practical terms.
PRODUKTBESKRIVELSE
Linear Algebra for Data Science, Machine Learning, and Signal Processing Hardcover – 16 May 2024
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Kundespørgsmal & svar
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spørgsmål:
Who is this textbook intended for?
svar: It is perfect for upper-level undergraduates and first-year graduate students with prior linear algebra knowledge. -
spørgsmål:
Does the book include exercises for students?
svar: Yes, it includes over 200 multiple-choice questions and homework exercises with solutions. -
spørgsmål:
Are there practical applications included in the book?
svar: Absolutely, it highlights various applications such as low-rank approximation, logistic regression, and dimensionality reduction.
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Fordele
- Comprehensive coverage of topics
- Accessible to beginners
- Clear explanations and examples
- Useful for various applications
- Well-structured and organized
Ulemper
- Some advanced topics may require further study.
Produktets prishistorik
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DKK 992
Bestil nu og få den omkring Tirsdag, Juni 30
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Sikker transaktion
Ubuy arbejder hårdt for at beskytte din sikkerhed og dit privatliv. Vores avancerede betalingssikkerhedssystem sikrer fortrolighed ved at kryptere dine oplysninger under transmission ved hjælp af AES (Advanced Encryption Standards) og SSL (Secure Socket Layer) protokoller. Dine betalingsoplysninger er 100% sikre, da vi ikke deler dine betalingsoplysninger med tredjepartssælgere.
Vores bedste logistikpartnere
Hurtigste grænseoverskridende levering
Egenskaber og fordele
- Engaging textbook designed for upper-level undergraduates and first-year graduate students.
- Covers both basic and advanced matrix topics relevant to data science and machine learning.
- Includes 200+ multiple-choice questions for interactive classroom learning.
- Features practical exercises with solutions available for instructors.
- Encourages active learning through 'explore' questions and practical Julia code examples.
- Offers a suite of computational notebooks for hands-on learning experiences.