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The Handbook of Data Science and AI: Generate Value from Data with Machine Learning and Data Analytics
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.
- 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 projects
The 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
- Mathematics Mathematics for Machine Learning to help you understand and utilize various ML algorithms. - Machine From statistical to neural and from Transformers and GPT-3 to AutoML, we introduce common frameworks for applying ML in practice - Natural Language Tools and techniques for gaining insights from text data and developing language technologies - Computer How can we gain insights from images and videos with data science? - Modeling and 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 How to turn experimentation into a working data science product? - Presenting your Essential presentation techniques for data scientists
- 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 projects
The 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
- Mathematics Mathematics for Machine Learning to help you understand and utilize various ML algorithms. - Machine From statistical to neural and from Transformers and GPT-3 to AutoML, we introduce common frameworks for applying ML in practice - Natural Language Tools and techniques for gaining insights from text data and developing language technologies - Computer How can we gain insights from images and videos with data science? - Modeling and 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 How to turn experimentation into a working data science product? - Presenting your Essential presentation techniques for data scientists
576 pages, Hardcover
Published April 28, 2022
12 people are currently reading
24 people want to read
About the author
Stefan Papp
15 books11 followersAuthor of four books... Now an avid reader. I live in Armenia, where I enjoy a great culture.
Not yet decided if I want to write a book again
Not yet decided if I want to write a book again
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Displaying 1 of 1 review
April 3, 2023
Recht interessant, allerdings hätte ich mir stellenweise gewünscht, dass besonders die Praxisbeispiele etwas mehr in die Tiefe gehen. Stellenweise wirkte mir das ganze etwas zu theoretisch im Sinne von "Die Daten könnte man vielleicht so oder so einsetzen", was für den Praxisteil etwas enttäuschen ist.
Displaying 1 of 1 review