Math for Programming
Apr 2025 · No Starch Press
eBook
504
Halaman
family_home
Memenuhi syarat
info
infoBuku ini akan tersedia pada tanggal 22 April 2025. Anda tidak akan ditagih hingga buku tersebut dirilis.
Tentang eBook ini
A one-stop-shop for all the math you should have learned for your programming career.
Every great programming challenge has mathematical principles at its heart. Whether you’re optimizing search algorithms, building physics engines for games, or training neural networks, success depends on your grasp of core mathematical concepts.
In Math for Programming, you’ll master the essential mathematics that will take you from basic coding to serious software development. You’ll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms.
Through clear explanations and practical examples, you’ll learn to:
Whether you’re seeking to fill gaps in your mathematical foundation or looking to refresh your understanding of core concepts, Math for Programming will turn complex math into a practical tool you’ll use every day.
Every great programming challenge has mathematical principles at its heart. Whether you’re optimizing search algorithms, building physics engines for games, or training neural networks, success depends on your grasp of core mathematical concepts.
In Math for Programming, you’ll master the essential mathematics that will take you from basic coding to serious software development. You’ll discover how vectors and matrices give you the power to handle complex data, how calculus drives optimization and machine learning, and how graph theory leads to advanced search algorithms.
Through clear explanations and practical examples, you’ll learn to:
- Harness linear algebra to manipulate data with unprecedented efficiency
- Apply calculus concepts to optimize algorithms and drive simulations
- Use probability and statistics to model uncertainty and analyze data
- Master the discrete mathematics that powers modern data structures
- Solve dynamic problems through differential equations
Whether you’re seeking to fill gaps in your mathematical foundation or looking to refresh your understanding of core concepts, Math for Programming will turn complex math into a practical tool you’ll use every day.
Tentang pengarang
Ronald T. Kneusel has been working with machine learning in industry since 2003 and has a PhD in machine learning from the University of Colorado, Boulder. Kneusel is the author of Practical Deep Learning, Math for Deep Learning, The Art of Randomness, How AI Works, and Strange Code (all from No Starch Press), as well as Numbers and Computers and Random Numbers and Computers (Springer).
Informasi bacaan
Smartphone dan tablet
Instal aplikasi Google Play Buku untuk Android dan iPad/iPhone. Aplikasi akan disinkronkan secara otomatis dengan akun Anda dan dapat diakses secara online maupun offline di mana saja.
Laptop dan komputer
Anda dapat mendengarkan buku audio yang dibeli di Google Play menggunakan browser web komputer.
eReader dan perangkat lainnya
Untuk membaca di perangkat e-ink seperti Kobo eReaders, Anda perlu mendownload file dan mentransfernya ke perangkat Anda. Ikuti petunjuk Pusat bantuan yang mendetail untuk mentransfer file ke eReaders yang didukung.
