BOOKS - Data Structures for Engineers and Scientists Using Python
Data Structures for Engineers and Scientists Using Python - Rakesh Nayak, Nishu Gupta 2025 PDF CRC Press BOOKS
ECO~18 kg CO²

1 TON

Views
31916

Telegram
 
Data Structures for Engineers and Scientists Using Python
Author: Rakesh Nayak, Nishu Gupta
Year: 2025
Pages: 410
Format: PDF
File size: 10.1 MB
Language: ENG



Pay with Telegram STARS
Data Structures for Engineers and Scientists Using Python In today's fast-paced technological world, it is essential to stay updated with the latest advancements in technology to survive and thrive. This holds especially true for engineers and scientists who need to constantly evolve their knowledge and skills to remain relevant in their respective fields. One such essential aspect of technology evolution is data structures, which play a crucial role in software development and scientific computing. In his book "Data Structures for Engineers and Scientists Using Python author [Author Name] provides an in-depth understanding of data structures and their implementation using Python programming. The book caters to senior undergraduate and graduate students, as well as academic researchers in the fields of electrical engineering, electronics, computer engineering, and information technology. As the title suggests, the text focuses on the use of Python programming language to cover the fundamentals of data structures and their practical applications. The author has taken a unique approach by providing worked-out examples to help readers understand the concepts better. The text begins with an introduction to the basics of Python programming, making it accessible to those who are new to the language. It then delves into the core topics of data structures, including arrays, linked lists, stacks, queues, trees, and graphs. Each chapter provides a detailed explanation of the concepts along with examples that illustrate how they can be applied in real-world scenarios.
''

You may also be interested in:

Big Data and Analytics for Beginners: Navigating the World of Data-Driven Decision Making
Training Data for Machine Learning Human Supervision from Annotation to Data Science (Final)
Agile Data Science 2.0 Building Full-Stack Data Analytics Applications with Spark
Behavioral Data Analysis with R and Python Customer-Driven Data for Real Business Results
Tableau for Salesforce Visualise data and generate insights with the leading platforms for data analytics
Data Mesh Principles, Patterns, Architecture, and Strategies for Data-Driven Decision Making
Data Governance The Definitive Guide People, Processes, and Tools to Operationalize Data Trustworthiness
Data Science Essentials with R Learn with focus on data manipulation, visualization, and machine learning
Humanities Data in R Exploring Networks, Geospatial Data, Images, and Text, 2nd Edition
The Self-Service Data Roadmap Democratize Data and Reduce Time to insight (Early Release)
SQL for Data Analysis Advanced Techniques for Transforming Data into Insights (Early Release)
Humanities Data in R Exploring Networks, Geospatial Data, Images, and Text, 2nd Edition
Humanizing Big Data: Marketing at the Meeting of Data, Social Science and Consumer Insight
The Data Preparation Journey: Finding Your Way with R (Chapman and Hall CRC Data Science Series)
Data Mesh Principles, Patterns, Architecture, and Strategies for Data-Driven Decision Making
Data Centric Artificial Intelligence: A Beginner|s Guide (Data-Intensive Research)
Big Data, Small Devices Investigating the Natural World Using Real-Time Data
Univariate, Bivariate, and Multivariate Statistics Using R Quantitative Tools for Data Analysis and Data Science
The Real Work of Data Science Turning data into information, better decisions, and stronger organizations
Python for Data Analysis Data Wrangling with Pandas, NumPy, and IPython, 2nd Edition
Practical Data Science with SAP Machine Learning Techniques for Enterprise Data, First Edition
Learning Data Science Data Wrangling, Exploration, Visualization, and Modeling with Python (Final)
Data Universe Organizational Insights with Python Embracing Data Driven Decision Making
Data Universe Organizational Insights with Python Embracing Data Driven Decision Making
R Graphics Essentials for Great Data Visualization +200 Practical Examples You Want to Know for Data Science
Big Data, Data Mining, and Machine Learning Value Creation for Business Leaders and Practitioners
Tableau for Salesforce Visualise data and generate insights with the leading platforms for data analytics
Data Warehouse and Data Mining: Concepts, techniques and real life applications (English Edition)
Python for Data Analysis Unlocking Insights and Driving Innovation with Powerful Data Techniques. 2 in 1 Guide
Web Data APIs for Knowledge Graphs Easing Access to Semantic Data for Application Developers
Data Sketches A journey of imagination, exploration, and beautiful data visualizations (AK Peters Visualization Series)
Big Data and Hadoop Fundamentals, tools, and techniques for data-driven success - 2nd Edition
Computer Science in Sport Modeling, Simulation, Data Analysis and Visualization of Sports-Related Data
Data Science in Chemistry: Artificial Intelligence, Big Data, Chemometrics and Quantum Computing with Jupyter
Apache Iceberg: The Definitive Guide: Data Lakehouse Functionality, Performance, and Scalability on the Data Lake
Programming Skills for Data Science Start Writing Code to Wrangle, Analyze, and Visualize Data with R
Big Data and Hadoop Fundamentals, tools, and techniques for data-driven success - 2nd Edition
Hands on Azure Data Studio Microsoft|s Open Platform for Data Engineering and Analytics
Computer Science in Sport: Modeling, Simulation, Data Analysis and Visualization of Sports-Related Data
Practical Synthetic Data Generation Balancing Privacy and the Broad Availability of Data (Early Release)