BOOKS - Introduction to Data Science
Introduction to Data Science - Gaoyan Ou, Zhanxing Zhu, Bin Dong 2024 PDF World Scientific Publishing BOOKS
ECO~18 kg CO²

1 TON

Views
51410

Telegram
 
Introduction to Data Science
Author: Gaoyan Ou, Zhanxing Zhu, Bin Dong
Year: 2024
Pages: 445
Format: PDF
File size: 32.9 MB
Language: ENG



Pay with Telegram STARS
Introduction to Data Science: A Comprehensive Guide to Understanding the Evolution of Technology and Its Impact on Humanity In today's fast-paced world, technology is advancing at an unprecedented rate, transforming every aspect of our lives. From smartphones to self-driving cars, technology has made our lives easier, more connected, and more efficient. However, this rapid evolution also brings about new challenges and concerns, such as data privacy, cybersecurity threats, and job displacement. In "Introduction to Data Science," we will delve into the process of technological development and its impact on humanity, exploring the need to study and understand the process of technology evolution and its implications for our future. The Book's Purpose The purpose of "Introduction to Data Science" is to provide readers with a comprehensive understanding of the evolution of technology and its effects on society. The book aims to educate readers on the importance of developing a personal paradigm for perceiving the technological process of developing modern knowledge, as well as the need for unity among people in a warring state.
''

You may also be interested in:

Scaling Python with Dask From Data Science to Machine Learning (Final)
Web and Network Data Science Modeling Techniques in Predictive Analytics
Data Science на службе бизнеса. Книга об интеллектуальном анализе данных
Marketing Analytics Optimize Your Business with Data Science in R, Python, and SQL
Data Science на службе бизнеса. Книга об интеллектуальном анализе данных
Linear Algebra for Data Science, Machine Learning, and Signal Processing
Python Data Science Handbook, 2nd Edition (Early Release)
Information-Driven Machine Learning Data Science as an Engineering Discipline
Graph Algorithms for Data Science With examples in Neo4j (Final Release)
Data Science. Инсайдерская информация для новичков. Включая язык R
Data Science and Machine Learning for Non-Programmers Using SAS Enterprise Miner
Data Structures and Abstractions with Java Fifth Edition (What|s New in Computer Science)
Football Analytics with Python and R: Learning Data Science Through the Lens of Sports
Data Science in Engineering and Management Applications, New Developments, and Future Trends
Data Science at the Command Line, 2nd Edition (Early Release)
Graph Algorithms for Data Science With examples in Neo4j (Final Release)
Data Science in Production Building Scalable Model Pipelines with Python
Cyber-Physical Systems Data Science, Modelling and Software Optimization
Linear Algebra for Data Science, Machine Learning, and Signal Processing
Scaling Python with Dask From Data Science to Machine Learning (Final)
Introduction to Multidisciplinary Science with Artificial Intelligence Geodesy, Geotherms, Quantum Entanglement, and Spectroscopy
Introduction to Multidisciplinary Science with Artificial Intelligence Geodesy, Geotherms, Quantum Entanglement, and Spectroscopy
Learn to Program with Scratch A Visual Introduction to Programming with Games, Art, Science, and Math
Introduction to Multidisciplinary Science with Artificial Intelligence: Geodesy, Geotherms, Quantum Entanglement, and Spectroscopy
Implementing Data Mesh Design, Build, and Implement Data Contracts, Data Products, and Data Mesh
Implementing Data Mesh Design, Build, and Implement Data Contracts, Data Products, and Data Mesh
Velocity-Based Training How to Apply Science, Technology, and Data to Maximize Performance
Data Science on the Google Cloud Platform, Second Edition (2nd Early Release)
Exam Ref DP-100 Designing and Implementing a Data Science Solution on Azure
Quantitative Analysis for System Applications Data Science and Analytics Tools and Techniques
Data-Driven Science and Engineering Machine Learning, Dynamical Systems, and Control
Data Science in R A Case Studies Approach to Computational Reasoning and Problem Solving
Data Science Solutions on Azure The Rise of Generative AI and Applied AI, 2nd Edition
Business Intelligence, Analytics, Data Science, and AI A Managerial Perspective, 5th Edition
Python Data Science Learn the Ethics of Coding in a Day by Taking My Classes
Why Data Science Projects Fail The Harsh Realities of Implementing AI and Analytics, without the Hype
Future Communication Systems Using Artificial Intelligence, Internet of Things and Data Science
Data Science at the Command Line Facing the Future with Time-Tested Tools
AI for Data Science Artificial Intelligence Frameworks and Functionality for Deep Learning, Optimization, and Beyond
Geospatial Data Science Essentials: 101 Practical Python Tips and Tricks