- Home Page /
- Books /
- Science, Nature & Maths /
- Engineering & Technology /
- Electronics & Communications Engineering /
- Telecommunications /
- Linear Algebra for Data Science, Machine Lear...
Item #:
112607187
Linear Algebra for Data Science, Machine Learning, and Signal Processing Hardcover – 16 May 2024
Item #:
112607187
PLN 345
Price Details
Excluding Shipping & Custom charges ( Shipping and custom charges will be calculated on checkout )
*All items will import from UK
0 ratings
Write a review
In stock
Imported from UK store
QTY:
Order now and get it around Tuesday, June 30
Secured 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
Maximise student engagement and understanding of matrix methods in data-driven applications with this modern teaching package.
Fast
Shipping
Free
Return*
Secure Packaging
100% Original Products
PCI DSS Compliance
ISO 27001 Certified
What Stands Out
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.
Product Details
| Item Weight | 2 lbs (910 grams) |
Who Should Buy?
-
Data Science Students
Students pursuing data science will benefit from foundational linear algebra skills necessary for data analysis and modeling.
-
Machine Learning Practitioners
Practitioners looking to deepen their understanding of machine learning algorithms will find valuable insights in this text.
-
Signal Processing Engineers
Engineers working in signal processing will appreciate the practical applications of linear algebra in their field.
-
Beginners in Mathematics
Complete novices in mathematics may struggle with the complex concepts presented without prior foundational knowledge.
-
Casual Learners
Individuals seeking a light introduction to linear algebra might find this textbook too dense and technical.
-
Non-Technical Readers
Readers without a technical background may find the content difficult to understand and apply in practical terms.
Product Description
Linear Algebra for Data Science, Machine Learning, and Signal Processing Hardcover – 16 May 2024
Have any Query? Chat with us
Customer Questions & Answers
-
Question:
Who is this textbook intended for?
Answer: It is perfect for upper-level undergraduates and first-year graduate students with prior linear algebra knowledge. -
Question:
Does the book include exercises for students?
Answer: Yes, it includes over 200 multiple-choice questions and homework exercises with solutions. -
Question:
Are there practical applications included in the book?
Answer: Absolutely, it highlights various applications such as low-rank approximation, logistic regression, and dimensionality reduction.
Telecommunications Editorial Review
No editorial reviews found
Customer Reviews & Ratings
1 customers ratings
-
5 Star
100%
-
4 Star
0%
-
3 Star
0%
-
2 Star
0%
-
1 Star
0%
Review this product
Share your thoughts with other customers
Pros
- Comprehensive coverage of topics
- Accessible to beginners
- Clear explanations and examples
- Useful for various applications
- Well-structured and organized
Cons
- Some advanced topics may require further study.
Product Price History
Important information
- Limitations : For products shipped internationally, please note that any manufacturer warranty may not be valid; manufacturer service options may not be available; product manuals, instructions, and safety warnings may not be in destination country languages; the products (and accompanying materials) may not be designed in accordance with destination country standards, specifications, and labeling requirements; and the products may not conform to destination country voltage and other electrical standards (requiring use of an adapter or converter if appropriate). The recipient is responsible for assuring that the product can be lawfully imported to the destination country. When ordering from Ubuy or its affiliates, the recipient is the importer of record and must comply with all laws and regulations of the destination country.
- Not all the products listed on Ubuy are for sale, as Ubuy is a global search engine. Products are subject to export/trade regulations.
PLN 345
Order now and get it around Tuesday, June 30
This item is not restrict in my country.(Please click on above link if this item is not restrict in your country, So our team will review and allow.)
QTY:
Secured 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
Fastest cross-border delivery
Features & Benefits
- 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.