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The Handbook of Data Science and AI: Generate Value from Data with Machine Learning and Data Analytics, Papp Stefan, Weidinger Wolfgang, Munro Katherine


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Автор: Papp Stefan, Weidinger Wolfgang, Munro Katherine
Название:  The Handbook of Data Science and AI: Generate Value from Data with Machine Learning and Data Analytics
ISBN: 9781569908860
Издательство: Mare Nostrum (Eurospan)
Классификация:

ISBN-10: 1569908869
Обложка/Формат: Paperback
Страницы: 573
Вес: 1.09 кг.
Дата издания: 30.09.2022
Язык: English
Размер: 172 x 246 x 36
Ключевые слова: Data analysis: general,Machine learning
Подзаголовок: Generate value from data with data analysis and machine learning
Рейтинг:
Поставляется из: Англии
Описание: Data Science, Big Data, and Artificial Intelligence are currently some of the most talked-about concepts in industry, government, and society, and yet also the most misunderstood. This book will clarify these concepts and provide you with practical knowledge to apply them. Featuring:- A comprehensive overview of the various fields of application of data science- Case studies from practice to make the described concepts tangible- Practical examples to help you carry out simple data analysis projectsThe book approaches the topic of data science from several sides. Crucially, it will show you how to build data platforms and apply data science tools and methods. Along the way, it will help you understand - and explain to various stakeholders - how to generate value from these techniques, such as applying data science to help organizations make faster decisions, reduce costs, and open up new markets. Furthermore, it will bring fundamental concepts related to data science to life, including statistics, mathematics, and legal considerations. Finally, the book outlines practical case studies that illustrate how knowledge generated from data is changing various industries over the long term. Contains these current issues:- Mathematics basics: Mathematics for Machine Learning to help you understand and utilize various ML algorithms.- Machine Learning: From statistical to neural and from Transformers and GPT-3 to AutoML, we introduce common frameworks for applying ML in practice- Natural Language Processing: Tools and techniques for gaining insights from text data and developing language technologies- Computer vision: How can we gain insights from images and videos with data science?- Modeling and Simulation: Model the behavior of complex systems, such as the spread of COVID-19, and do a What-If analysis covering different scenarios.- ML and AI in production: How to turn experimentation into a working data science product?- Presenting your results: Essential presentation techniques for data scientistsContributors: Stefan Papp / Wolfgang Weidinger / Katherine Munro / Bernhard Ortner / Annalisa Cadonna / Georg Langs / Roxane Licandro / Mario Meir-Huber / Danko Nikoli? / Zoltan Toth / Barbora Vesela / Rania Wazir / G?nther Zauner
Дополнительное описание: Machine learning|Data science and analysis: general



Linear Algebra and Learning from Data

Автор: Strang Gilbert
Название: Linear Algebra and Learning from Data
ISBN: 0692196382 ISBN-13(EAN): 9780692196380
Издательство: Cambridge Academ
Рейтинг:
Цена: 9978.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

Handbook of Big Data Analytics and Forensics

Автор: Choo Kim-Kwang Raymond, Dehghantanha Ali
Название: Handbook of Big Data Analytics and Forensics
ISBN: 3030747522 ISBN-13(EAN): 9783030747527
Издательство: Springer
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Цена: 25155.00 р.
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Описание: This handbook discusses challenges and limitations in existing solutions, and presents state-of-the-art advances from both academia and industry, in big data analytics and digital forensics. The second chapter comprehensively reviews IoT security, privacy, and forensics literature, focusing on IoT and unmanned aerial vehicles (UAVs). The authors propose a deep learning-based approach to process cloud’s log data and mitigate enumeration attacks in the third chapter. The fourth chapter proposes a robust fuzzy learning model to protect IT-based infrastructure against advanced persistent threat (APT) campaigns. Advanced and fair clustering approach for industrial data, which is capable of training with huge volume of data in a close to linear time is introduced in the fifth chapter, as well as offering an adaptive deep learning model to detect cyberattacks targeting cyber physical systems (CPS) covered in the sixth chapter. The authors evaluate the performance of unsupervised machine learning for detecting cyberattacks against industrial control systems (ICS) in chapter 7, and the next chapter presents a robust fuzzy Bayesian approach for ICS’s cyber threat hunting. This handbook also evaluates the performance of supervised machine learning methods in identifying cyberattacks against CPS. The performance of a scalable clustering algorithm for CPS’s cyber threat hunting and the usefulness of machine learning algorithms for MacOS malware detection are respectively evaluated. This handbook continues with evaluating the performance of various machine learning techniques to detect the Internet of Things malware. The authors demonstrate how MacOSX cyberattacks can be detected using state-of-the-art machine learning models. In order to identify credit card frauds, the fifteenth chapter introduces a hybrid model. In the sixteenth chapter, the editors propose a model that leverages natural language processing techniques for generating a mapping between APT-related reports and cyber kill chain. A deep learning-based approach to detect ransomware is introduced, as well as a proposed clustering approach to detect IoT malware in the last two chapters. This handbook primarily targets professionals and scientists working in Big Data, Digital Forensics, Machine Learning, Cyber Security Cyber Threat Analytics and Cyber Threat Hunting as a reference book. Advanced level-students and researchers studying and working in Computer systems, Computer networks and Artificial intelligence will also find this reference useful.

Machine Intelligence and Big Data Analytics for Cybersecurity Applications

Автор: Maleh Yassine, Shojafar Mohammad, Alazab Mamoun
Название: Machine Intelligence and Big Data Analytics for Cybersecurity Applications
ISBN: 3030570266 ISBN-13(EAN): 9783030570262
Издательство: Springer
Рейтинг:
Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis.

The 2020 International Conference on Machine Learning and Big Data Analytics for Iot Security and Privacy: Spiot-2020, Volume 2

Автор: Macintyre John, Zhao Jinghua, Ma Xiaomeng
Название: The 2020 International Conference on Machine Learning and Big Data Analytics for Iot Security and Privacy: Spiot-2020, Volume 2
ISBN: 3030627454 ISBN-13(EAN): 9783030627454
Издательство: Springer
Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Session 5: Data-driven co-design of communication, computing and control for IoT security

Design of a Force Balance Geophone Utilizing Bandwidth Extension and Data Acquisition Interface

Application of 3ds Max Technology in Archaeology

The Application of Virtual Reality Technology in ESP Teaching

Application of Simulation Method Based on Computer Bionic Design

The Implementation and Application of Computer Simulation Technology in PE Teaching

Construction of College Communities in the New Media Based on Network Environment

Political and Ideological Personnel Management Mode Based on Computer Network

Analysis of Mapping Knowledge Domain on Health and Wellness Tourism in the Perspective of Cite Space

Application of Smart Retail Mode in Suning.Com

Construction and Development of High-tech Smart City

Design and Implementation of Self-Service Tourism Management Information System Based on B/S Architecture

Chinese Culture Penetration in Teaching Chinese as a Foreign Language in the Era of Mobile Internet

Application and Outlook of Digital Media Technology in Smart Tourism

Accounting Informationization in Computer Network Environment

Mobile Phone GPS and Sensor Technology in College Students' Extracurricular Exercises

Design of Networking Network Model Based on Network Function Virtualization Technology

Intelligent Media Technology Empowered Brand Communication of Chinese Intangible Cultural Heritage

Construction Strategy of Smart English Teaching Platform from the Perspective of "Internet + Education"

Online Writing Effectiveness under the Blended Teaching Mode of Moscotech APP

A Narrative Environment Model for the Sustainability of Intangible Cultural Heritage under the 5G Era

Application Study of VPN on the Network of Hydropower Plant

Prediction of Technology Trend of Educational Robot Industry Based On Patent Map Analysis

Coal Handling System of Power Plant Based On PLC

Discussion on the Construction of Wireless Campus Network Based On SDN Architecture

Applicational Status Analysis of Artificial Intelligence Technology in Middle School Education and Teaching

Virtual Enterprise Partner Selection by Improved Analytic Hierarchy Process with Entropy Weight and Range Method

Research and implementation of Intelligent Tourism Guide System Based on cloud computing platform

Analysis of financial needs of new agricultural operators based on K-means clustering algorithm

Research on the application of virtual network technology in computer network security

Application of Bionics in Underwater Acoustic Covert Communication

Energy-saving and efficient underwater wireless sensor network security data aggregation model

False Data Filtering in Underwater Wireless Sensor Networks

Research on Underwater Bionic Covert Communication

Session 6: Authentication and access control for data usage in IoT

The Application of Virtual Reality Technology in Architectural Design

Computer-assisted Teaching and Cultivate Students' Innovative Thinking Ability

The Reform Progress and Practical Difficulties of State-owned Hospitals under Information Age―Case Analysis Based on the Reform in a Medical Institution of A Group in China

Financing Efficiency of SMEs in New Third Board Market in the Information Times

Application of Virtual Instrument Technology in Electronic Course Teaching

A Solution for Internet of Things based on Blockchain and Edge Computer

Discovery and Advice of Free Charging of Electronic Devices

Design and Implementation of Tourism Information Management System Based on .NET

A Computer Model for Decision of Equipment Maintenance Spare Parts Reserve

Risk Level Determination of Science a

Data Science and Big Data Analytics: A Step by Step Guide to learn data science from Scratch with Python Machine Learning and Big Data

Автор: Park Andrew
Название: Data Science and Big Data Analytics: A Step by Step Guide to learn data science from Scratch with Python Machine Learning and Big Data
ISBN: 1801779554 ISBN-13(EAN): 9781801779555
Издательство: Неизвестно
Рейтинг:
Цена: 4824.00 р.
Наличие на складе: Нет в наличии.

Описание:

★ 55% OFF for Bookstores NOW at $ 34,97 instead of $ 44.97 LAST DAYS ★



Your Customers Never Stop to Use this Awesome book


Do you want to know everything about Data science?

This guidebook is going to provide you with all of the information that you need to learn more about data science, what this process is all about, and how you can use the Python language to put it all to work for you Even if you have no idea how to program or any idea of what to do with all of that data you have been collecting, this guidebook will give you all of the tools you need to be successful

There are a lot of different parts that come with data science and being able to put them all together can really help us to do better with helping our customers, finding new products to bring to market, and more. And with the help of this guidebook, we can hopefully find the best ways to beat out the competition and see the results that will work for us. It takes some time, and a good data analysis with the right algorithms from Python, but it can be one of the best ways to make some smart and sound decisions for your business.

Working with data science is becoming even more prevalent as the years go on, and businesses all over the world, and in many different industries, are using this to help them see more success. Whether you want to make predictions, provide better customer service, or learn other valuable insights about your business, data science with the help of Python, can make this happen. When you are ready to see what Python data science can do for your business, make sure to check out this guidebook to get started.

The process of Python data science is not an easy one and learning how to make this work for your needs, and to put all of the parts together can make a big difference in the way that you run your business, and how much success you will see when it comes to your business growing in the future. When you are ready to learn more about working with Python data science and how to make this work for your business, make sure to check out this guidebook to get started.

There are so many parts that come with a data science project, and we are going to take some time to discuss them all in this guidebook. We are going to look at some of the basics that come with this data science project, and why it is so beneficial to so many companies to at least check it out and see what it has to offer them. At the same time, we are also going to explore how to set up your own environment to get started with data science, and some of the best libraries that are out there to help us succeed with the use of data science and Python put together.

This book covers:

  • What Is Data Science?
  • How Can I Use Data Science?
  • The Best Python Libraries for Data Science
  • Setting Up Your Virtual Environments for Data Science
  • The Importance of the NumPy Arrays
  • Gathering and Collecting Your Data
  • Loading and Preparing Your Dataset
  • Data Mining
  • Completing the Data Analysis
  • How Machine Learning Can Help
  • How to Work with Data Visualization

Many businesses are able to benefit when they work with data analysis for some of their own needs. It will help them to learn more about their customers, their industry, and so much more. When you are ready to learn more about what data science can do for you and to figure out whether this is a process your business should spend some time on, make sure to check out this guidebook to help you get started.


Buy it NOW and get addicted to this amazing book

Machine Intelligence and Big Data Analytics for Cybersecurity Applications

Автор: Maleh Yassine, Shojafar Mohammad, Alazab Mamoun
Название: Machine Intelligence and Big Data Analytics for Cybersecurity Applications
ISBN: 3030570231 ISBN-13(EAN): 9783030570231
Издательство: Springer
Цена: 27950.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book presents the latest advances in machine intelligence and big data analytics to improve early warning of cyber-attacks, for cybersecurity intrusion detection and monitoring, and malware analysis.

Machine Learning and Data Mining for Sports Analytics: 8th International Workshop, MLSA 2021, Virtual Event, September 13, 2021, Revised Selected Pape

Автор: Brefeld Ulf, Davis Jesse, Van Haaren Jan
Название: Machine Learning and Data Mining for Sports Analytics: 8th International Workshop, MLSA 2021, Virtual Event, September 13, 2021, Revised Selected Pape
ISBN: 303102043X ISBN-13(EAN): 9783031020438
Издательство: Springer
Рейтинг:
Цена: 11179.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the refereed post-conference proceedings of the 8th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2021, held as virtual event in September 2021.

AI and Machine Learning Paradigms for Health Monitoring System: Intelligent Data Analytics

Автор: Malik Hasmat, Fatema Nuzhat, Alzubi Jafar A.
Название: AI and Machine Learning Paradigms for Health Monitoring System: Intelligent Data Analytics
ISBN: 9813344113 ISBN-13(EAN): 9789813344112
Издательство: Springer
Цена: 25155.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book embodies principles and applications of advanced soft computing approaches in engineering, healthcare and allied domains directed toward the researchers aspiring to learn and apply intelligent data analytics techniques.

Feature engineering for machine learning and data analytics

Название: Feature engineering for machine learning and data analytics
ISBN: 0367571854 ISBN-13(EAN): 9780367571856
Издательство: Taylor&Francis
Рейтинг:
Цена: 6889.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Edited by two of the leading experts in the field, this book provides a comprehensive reference book on feature engineering. The book provides a description of problems and applications for feature engineering, as well as its techniques, principles, issues, and challenges.

Machine Learning and Data Mining for Sports Analytics

Автор: Ulf Brefeld; Jesse Davis; Jan Van Haaren; Albrecht
Название: Machine Learning and Data Mining for Sports Analytics
ISBN: 3030172732 ISBN-13(EAN): 9783030172732
Издательство: Springer
Рейтинг:
Цена: 6986.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This book constitutes the refereed post-conference proceedings of the 5th International Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2018, colocated with ECML/PKDD 2018, in Dublin, Ireland, in September 2018.

The 12 full papers presented together with 4 challenge papers were carefully reviewed and selected from 24 submissions. The papers present a variety of topics, covering the team sports American football, basketball, ice hockey, and soccer, as well as the individual sports cycling and martial arts. In addition, four challenge papers are included, reporting on how to predict pass receivers in soccer.
The Data Catalog: Sherlock Holmes Data Sleuthing for Analytics

Автор: O`Neil Bonnie K., Fryman Lowell
Название: The Data Catalog: Sherlock Holmes Data Sleuthing for Analytics
ISBN: 1634627873 ISBN-13(EAN): 9781634627870
Издательство: Gazelle Book Services
Рейтинг:
Цена: 8578.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: Apply this definitive guide to data catalogs and select the feature set needed to empower your data citizens in their quest for faster time to insight. The data catalog may be the most important breakthrough in data management in the last decade, ranking alongside the advent of the data warehouse. The latter enabled business consumers to conduct their own analyses to obtain insights themselves. The data catalog is the next wave of this, empowering business users even further to drastically reduce time to insight, despite the rising tide of data flooding the enterprise. Use this book as a guide to provide a broad overview of the most popular Machine Learning (ML) data catalog products, and perform due diligence using the extensive features list. Consider graphical user interface (GUI) design issues such as layout and navigation, as well as scalability in terms of how the catalog will handle your current and anticipated data and metadata needs. ONeil & Frymanpresent a typology which ranges from products that focus on data lineage, curation and search, data governance, data preparation, and of course, the core capability of finding and understanding the data. The authors emphasize that machine learning is being adopted in many of these products, enabling a more elegant data democratization solution in the face of the burgeoning mountain of data that is engulfing organizations. Derek Strauss, Chairman/CEO, Gavroshe, and Former CDO, TD Ameritrade. This book is organized into three sections: Chapters 1 and 2 reveal the rationale for a data catalog and share how data scientists, data administrators, and curators fare with and without a data catalog; Chapters 3-10 present the many different types of data catalogs; Chapters 11 and 12 provide an extensive features list, current trends, and visions for the future.

Data Science and Big Data Analytics: A Step by Step Guide to learn data science from Scratch with Python Machine Learning and Big Data

Автор: Park Andrew
Название: Data Science and Big Data Analytics: A Step by Step Guide to learn data science from Scratch with Python Machine Learning and Big Data
ISBN: 180177952X ISBN-13(EAN): 9781801779524
Издательство: Неизвестно
Рейтинг:
Цена: 3168.00 р.
Наличие на складе: Нет в наличии.

Описание:

★ 55% OFF for Bookstores NOW at $ 22,97 instead of $ 32.97 LAST DAYS ★


Your Customers Never Stop to Use this Awesome book


Do you want to know everything about Data science?

This guidebook is going to provide you with all of the information that you need to learn more about data science, what this process is all about, and how you can use the Python language to put it all to work for you Even if you have no idea how to program or any idea of what to do with all of that data you have been collecting, this guidebook will give you all of the tools you need to be successful

There are a lot of different parts that come with data science and being able to put them all together can really help us to do better with helping our customers, finding new products to bring to market, and more. And with the help of this guidebook, we can hopefully find the best ways to beat out the competition and see the results that will work for us. It takes some time, and a good data analysis with the right algorithms from Python, but it can be one of the best ways to make some smart and sound decisions for your business.

Working with data science is becoming even more prevalent as the years go on, and businesses all over the world, and in many different industries, are using this to help them see more success. Whether you want to make predictions, provide better customer service, or learn other valuable insights about your business, data science with the help of Python, can make this happen. When you are ready to see what Python data science can do for your business, make sure to check out this guidebook to get started.

The process of Python data science is not an easy one and learning how to make this work for your needs, and to put all of the parts together can make a big difference in the way that you run your business, and how much success you will see when it comes to your business growing in the future. When you are ready to learn more about working with Python data science and how to make this work for your business, make sure to check out this guidebook to get started.

There are so many parts that come with a data science project, and we are going to take some time to discuss them all in this guidebook. We are going to look at some of the basics that come with this data science project, and why it is so beneficial to so many companies to at least check it out and see what it has to offer them. At the same time, we are also going to explore how to set up your own environment to get started with data science, and some of the best libraries that are out there to help us succeed with the use of data science and Python put together.

This book covers:

  • What Is Data Science?
  • How Can I Use Data Science?
  • The Best Python Libraries for Data Science
  • Setting Up Your Virtual Environments for Data Science
  • The Importance of the NumPy Arrays
  • Gathering and Collecting Your Data
  • Loading and Preparing Your Dataset
  • Data Mining
  • Completing the Data Analysis
  • How Machine Learning Can Help
  • How to Work with Data Visualization

Many businesses are able to benefit when they work with data analysis for some of their own needs. It will help them to learn more about their customers, their industry, and so much more. When you are ready to learn more about what data science can do for you and to figure out whether this is a process your business should spend some time on, make sure to check out this guidebook to help you get started.


Buy it NOW and get addicted to this amazing book


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