Introduction To Machine Learning – alle Bücher

Ruye Wang
Introduction to Machine Learning

"Explore how and why machine learning algorithms work with this self-contained, hands-on textbook for senior undergraduate and graduate students. Using Matlab and Python, it includes over 85 worked e…

lieferbar ab 31.7.2025.

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Pramod Gupta, John M. Acken, Naresh Kumar Sehgal
Introduction to Machine Learning with Security

This book provides an introduction to machine learning, security and cloud computing, from a conceptual level, along with their usage with underlying infrastructure. The authors emphasize fundamentals and…

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R Kelly Rainer
Introduction to Artificial Intelligence and Machine Learning, with eBook Access Code

Helps students unlock the power of AI and Machine Learning to achieve business success and future-proof their careersArtificial intelligence and machine learning are transforming the modern workplace, mak…

lieferbar ab 3.9.2025.

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Marcus J. Neuer
Machine Learning for Engineers

Machine learning and artificial intelligence are ubiquitous terms for improving technical processes. However, practical implementation in real-world problems is often difficult and complex.This textbook e…

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Mehrdaad Ghorashi
Introduction to Machine Dynamics

This book introduces machine dynamics, an essential competency important for many applications such as designing robots for manufacturing/materials handling or the landing gear of an airplane, analyzing t…

lieferbar ab 16.8.2025.

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From Machine Learning to Artificial Intelligence

The world is on a cusp of something great. Technology has advanced from solving simple issues to complex issues in both human life and other aspects such as social, economic, and environmental issues. The…

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2 Bücher

Francesco Della Porta
From Satanic Mills to Machine Learning

The West brought two key changes to human endeavors: the mechanized factory system and the data processing automation. Each promoted globalization, later enabling the creation of oligopolies and causing a…

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Laura Mostert, Roy Lindelauf, V. S. Subrahmanian, Marnix Provoost
Machine Learning Techniques to Predict Terrorist Attacks

One of the most influential actors in spreading Islamist violence across the Sahel is Jama'at Nasr Al Islam Wal Muslimin (JNIM).This book provides the first systematic quantitative analysis of JNIM's beha…

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Kinky
Exploring Optimization Algorithms in Machine Learning: From Theory to Practice

Optimization algorithms in machine learning bridge theoretical foundations with practical applications, crucial for refining model performance. Techniques like gradient descent, stochastic gradient descen…

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Sanam
Machine Learning for Missing Maps: A Collaboration to Improve Disaster Relief

Disaster strikes, but where's the map? Traditional maps often lack details in vulnerable areas. Here's where machine learning (ML) and a collaborative project called Missing Maps team up to improve disast…

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David A Wood
Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems

Implementation and Interpretation of Machine and Deep Learning to Applied Subsurface Geological Problems: Prediction Models Exploiting Well-Log Information explores machine and deep learning models for su…

lieferbar innerhalb 1-2 Wochen

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Yannick Lingelbach
Application of Data Mining and Machine Learning Methods to Industrial Heat Treatment Processes for Hardness Prediction

This work presents a data mining framework applied to industrial heattreatment (bainitization and case hardening) aiming to optimize processes and reduce costs. The framework analyses factors such as mate…

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Crowd Dynamics, Volume 5

This contributed volume explores innovative research in the modeling, simulation, and control of crowd dynamics. Chapter authors approach the topic from the perspectives of mathematics, physics, engineeri…

lieferbar ab 1.11.2025.

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Carl Kingsford
An Introduction to String Algorithms

An essential introduction to the building blocks of modern text processingString algorithms make it possible to process, store, and manipulate text with computational efficiency, with applications ranging…

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Jeremy Budd, Yves van Gennip
Differential Equations and Variational Methods on Graphs

The burgeoning field of differential equations on graphs has experienced significant growth in the past decade, propelled by the use of variational methods in imaging and by its applications in machine le…

lieferbar ab 30.11.2025.

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Ilse Depraetere, Thierry Hamon, Clemens Hufeld, Benoît Leclercq
Models of Modals

Modal verbs in English communicate delicate shades of meaning, there being a large range of verbs both on the necessity side (must , have to , should , ought to , need , need to ) and the possibility side…

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Laurence Moroney
AI and ML for Coders in PyTorch

Eager to learn AI and machine learning but unsure where to start? Laurence Moroney's hands-on, code-first guide demystifies complex AI concepts without relying on advanced mathematics. Designed for progra…

lieferbar ab 31.7.2025.

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Edward Dongbo Cui
Vectorization

Enables readers to develop foundational and advanced vectorization skills for scalable data science and machine learning and address real-world problemsOffering insights across various domains such as com…

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Nico Michaelis
Dyslexia reading and writing disability

Self-Study including control questions and answers. Introduction to learning therapy Volume 1.Units 11 on 206 pages.You can find a detailed sample here: https://drive.google.com/file/d/1-KRtkJZu1i4llo4qDx…

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Anna Dawid, Alexandre Dauphin, Julian Arnold
Machine Learning in Quantum Sciences

This book provides an accessible introduction to machine learning and demonstrates its applications in the quantum sciences. Readers will be equipped with the necessary tools to engage with emerging liter…

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