Mathematical Methods in Data Science - Jingli Ren,Haiyan Wang
-35% su kodu BOOKS
Pristatymas per 10-16 d.d.
30 dienų grąžinimo politika
Mathematical Methods in Data Science introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for data analysis and prediction. The mathematics is accompanied with examples and problems arising in data science to demonstrate advanced mathematics, in particular, data-driven differential equations used. Chapters also cover netw ... Visas aprašymas
Jums taip pat gali patikti
TOP
If Anyone Builds It, Everyone Dies: Why Superhuman AI Would Kill Us All
Eliezer Yudkowsky, Nate Soares
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
How To Think About AI: A Guide For The Perplexed
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
Gödel, Escher, Bach: An Eternal Golden Braid
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
AI Engineering: Building Applications with Foundation Models
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
Empire of AI: Dreams and Nightmares in Sam Altman's OpenAI
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
Python Crash Course: A Hands-On, Project-Based Introduction to Programming
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
The Rust Programming Language
Steve Klabnik, Carol Nichols, Chris Krycho
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
How to Talk to AI: (And How Not To)
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
The Pragmatic Programmer: journey to mastery, 20th Anniversary Edition, 2/e: your journey to mastery, 20th Anniversary Edition
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
Hackers. 25th Anniversary Edition: Heroes of the Computer Revolution
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
The Art of Game Design: A Book of Lenses
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
How Linux Works: What Every Superuser Should Know
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
Hands-On Large Language Models: Language Understanding and Generation
Maarten Grootendorst, Jay Alammar
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
Fundamentals of Software Architecture: A Modern Engineering Approach
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
Speak Data: Artists, Scientists, Thinkers, and Dreamers on How We Live Our Lives in Numbers
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
Clean Architecture: A Craftsman's Guide to Software Structure and Design
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
World of Warcraft Chronicle, Volume 2
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
Linux Basics for Hackers, 2nd Edition: Getting Started with Networking, Scripting, and Security in Kali
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
TOP
Deep Learning: Foundations and Concepts
Christopher M. Bishop, Hugh Bishop
-35% su kodu BOOKS
Turime sandėlyje pas mūsų tiekėją
Aprašymas
Mathematical Methods in Data Science introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for data analysis and prediction. The mathematics is accompanied with examples and problems arising in data science to demonstrate advanced mathematics, in particular, data-driven differential equations used. Chapters also cover network analysis, ordinary and partial differential equations based on recent published and unpublished results. Finally, the book introduces a new approach based on network analysis to integrate big data into the framework of ordinary and partial differential equations for data analysis and prediction.
There are a number of books on mathematical methods in data science. Currently, all these related books primarily focus on linear algebra, optimization and statistical methods. However, network analysis, ordinary and partial differential equation models play an increasingly important role in data science. With the availability of unprecedented amount of clinical, epidemiological and social COVID-19 data, data-driven differential equation models have become more useful for infection prediction and analysis.
- Combines a broad spectrum of mathematics, including linear algebra, optimization, network analysis and ordinary and partial differential equations for data science
- Written by two researchers who are actively applying mathematical and statistical methods as well as ODE and PDE for data analysis and prediction
- Highly interdisciplinary, with content spanning mathematics, data science, social media analysis, network science, financial markets, and more
- Presents a wide spectrum of topics in a logical order, including probability, linear algebra, calculus and optimization, networks, ordinary differential and partial differential equations
Daugiau informacijos
| Autorius | Jingli Ren, Haiyan Wang |
|---|---|
| Leidėjas | Elsevier Science |
| Išleidimo metai | 2023 |
| Viršelio tipas | Minkšti viršeliai |
| EAN | 9780443186790 |