
Introduction to Data Science by Laura Igual
This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the interdisciplinary field of data science. The coverage spans key concepts from statistics, machine/deep learning and responsible data science, useful techniques for network analysis and natural language processing, and practical applications of data science such as recommender systems or sentiment analysis.
Topics and features:
- Provides numerous practical case studies using real-world data throughout the book
- Supports understanding through hands-on experience of solving data science problems using Python
- Describes concepts, techniques and tools for statistical analysis, machine learning, graph analysis, natural language processing, deep learning and responsible data science
- Reviews a range of applications of data science, including recommender systems and sentiment analysis of text data
- Provides supplementary code resources and data at an associated website
This practically-focused textbook provides an ideal introduction to the field for upper-tier undergraduate and beginning graduate students from computer science, mathematics, statistics, and other technical disciplines. The work is also eminently suitable for professionals on continuous education short courses, and to researchers following self-study courses.
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Modelling Computing Systems
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Sets, Logic and Maths for Computing
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Principles of Digital Image Processing
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Introduction to Artificial Intelligence
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A First Introduction to Quantum Computing and Information
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A Practical Approach to Compiler Construction
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A Concise Introduction to Languages and Machines
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Fundamentals of Discrete Math for Computer Science
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Data Structures and Algorithms with Python
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Mathematics for Computer Graphics
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A Beginners Guide to Python 3 Programming
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Philosophical and Cultural Aspects of Computing
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Principles of Data Mining
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Pattern Recognition
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Introduction to Deep Learning
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Financial Software Engineering
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Guide to Competitive Programming
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Advanced Guide to Python 3 Programming
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Introduction to Medical Image Analysis
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Introduction to Video and Image Processing
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Introduction to Software Quality
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Multicore Programming Using the ParC Language
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Introduction to HPC with MPI for Data Science
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Computability and Complexity
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Object-Oriented Programming Languages: Interpretation
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Introduction to Parallel Computing
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Concise Guide to Databases
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Human-Centred Scientific Data Visualisation
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Guide to Using Generative AI in Programming
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Programming in HTML and PHP
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Introduction to Cryptographic Definitions
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Proofs and Algorithms
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Introduction to Software Process Improvement
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Rigorous Software Development
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Sensing and Systems in Pervasive Computing
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Autonomic Computing
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OCaml Scientific Computing
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Applied Logic for Computer Scientists
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Basic Graph Theory
Dr. Laura Igual is an Associate Professor at the Departament de Matemàtiques i Informàtica, Universitat de Barcelona, Spain. Dr. Santi Seguí is an Associate Professor at the same institution.
The authors wish to mention that some chapters were co-written by Jordi Vitrià, Eloi Puertas, Petia Radeva, Oriol Pujol, Sergio Escalera.
| SKU | Unavailable |
| ISBN 13 | 9783031489556 |
| ISBN 10 | 3031489551 |
| Title | Introduction to Data Science |
| Author | Laura Igual |
| Series | Undergraduate Topics In Computer Science |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer International Publishing AG |
| Year published | 2024-04-13 |
| Number of pages | 246 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |






































