£185.00

CRC Press Data Science for Engineering: Principles, Tools, and Applications Across Disciplines

Name: Data Science for Engineering: Principles, Tools, and Applications Across Disciplines
Brand: CRC Press
Price: 185.0 GBP
Availability: InStock

AI & Machine Learning

It has never been this cheap. We have no record of a lower price.

£185 today · cheaper than every other day in the last 2 months

NEW HERE?

Amazon shows you one price. We show you all of them.

Tosheroon watches Amazon prices so you don't have to. Every product on Amazon has a price history — we make it visible. Set the price you'd actually pay, and we'll email you the second it gets there. No app, no account, one email.

WHAT'S ON THIS PAGE

↓ Price chart
when this has been cheap or pricey

↓ Forecast
where the price is heading next

↓ Statistics
all-time high & low, recent range

↑ Price alert
name your number, we'll email you

Price History & Forecast

Grey patches = out of stock. Cheaper = lower on the chart. Hover for exact prices.

Last 35 days · 35 data points (no recent data)

Historical

Generating forecast…

Price Distribution

Price distribution over 35 days • 1 price levels

Days at Price

Price Analysis

Most common price: £185 (35 days, 100.0%)

Price range: £185 - £185

Price levels: 1 different prices over 35 days

Description

This textbook provides a practical, engineering-focused introduction to modern data science. The book makes data science accessible to engineering students while maintaining the rigor necessary for advanced learners and professional practitioners. Data Science for Engineering: Principles, Tools, and Applications Across Disciplines delivers a systematic progression through essential data science competencies organized into four integrated parts. Part I establishes the foundations of engineering data science, covering the data science lifecycle, engineering data sources, preprocessing, data quality, and Python-based analysis. Part II develops the statistical foundations required for rigorous interpretation, including probability, statistical inference, and hypothesis testing. Part III focuses on feature engineering, feature selection, exploratory data analysis, and visualization techniques. Part IV presents the machine learning sequence for engineering applications, encompassing supervised learning, unsupervised learning, time series analysis, and deep learning methods such as convolutional neural networks and LSTM models. Throughout, concepts are developed with practical rigor and reinforced through realistic engineering datasets, worked examples, coding labs, and companion Jupyter notebooks. The book emphasizes not only how to apply data science methods but also when to use them, what assumptions they carry, and how to interpret their outputs responsibly in engineering decision-making contexts. This book is suited for undergraduate and graduate engineering students across all disciplines who are seeking to develop data science competencies for modern engineering practice. It also serves professional engineers and applied scientists who need to integrate data-driven approaches into their work. An Instructor's Solutions Manual is available to verified adopting instructors, along with downloadable Jupyter notebooks, datasets, and supplementary resources that support both teaching and self-directed learnin

Product Specifications

Brand: CRC Press
Format: hardcover
ASIN: 1041276257
Category: Books > Subjects > Computing & Internet > Computer Science > AI & Machine Learning
Domain: Amazon UK
Release Date: 18 December 2026
Listed Since: 23 July 2026

Barcode

No barcode data available

CRC Press Data Science for Engineering: Principles, Tools, and Applications Across Disciplines

It has never been this cheap. We have no record of a lower price.

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Handbook of Data Science with Semantic Technologies

Advancement in Engineering and Science: Recent Trends and Applications

Applied Research in Engineering Sciences

Data-Driven Systems and Intelligent Applications (Intelligent Data-Driven Systems and Artificial Intelligence)

The Data Science Handbook

Introduction to Product Design and Development for Engineers and Scientists

Electronics for Scientists

Artificial Intelligence and Data Science in Healthcare Applications (Computational and Intelligent Systems)

Advances in Sustainable Engineering: Innovations in Materials, Design, and Performance

Frontiers in Engineering, Science and Technology (Taylor and Francis Proceedings in Computer Science and Engineering)

Applied Intelligent Decision Making in Machine Learning (Computational Intelligence in Engineering Problem Solving)

System Safety Engineering and Risk Assessment: A Practical Approach

Trust, Security and Privacy for Big Data

Electric Power Distribution Engineering: International Student Edition

Mathematical Methods for Physics and Engineering: Practical Applications

Python for Data Science

Introduction to Semiconductor Devices for Engineering Students

Dairy Science and Technology

Advanced Data Analysis Techniques, Theory, and Applications

Raman and SERS Spectroscopy: Pioneering Diagnostics and New Horizons in Science and Engineering

AI and Renewable Energy Storage Synergy: Fundamentals and Applications (Sustainable Engineering and Science)

Textile Engineering: Statistical Techniques, Design of Experiments and Stochastic Modeling

Conceptual Modeling for Discrete-Event Simulation

Carbon Mitigation System Engineering: Principles, Methods and Practices