Thema Maschinelles Lernen – alle Bücher, Seite 7

Kristina Sekrst, Sandro Skansi
Introduction to Deep Learning

Undergraduate Topics in Computer Science

This textbook introduces deep learning in a style that is accessible, rigorous, and grounded in working code. It walks through the most widely used algorithms and architectures step by step, with mathemat…

lieferbar ab 8.8.2026.

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Liyu Shao, Qin Chen, Min He
AI in Banking

Big data and artificial intelligence (AI) cannot remain limited to academic theoretical research. It is crucial to utilize them in practical business scenarios, enabling cutting-edge technology to generat…

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Christian R Shelton
Introduction to Machine Learning

Aimed at undergraduate students, this text guides readers through the methods and principles of machine learning in an approachable manner without sacrificing mathematical precision or notation. Step-by-s…

lieferbar ab 30.11.2026.

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Christian R Shelton
Introduction to Machine Learning

Aimed at undergraduate students, this text guides readers through the methods and principles of machine learning in an approachable manner without sacrificing mathematical precision or notation. Step-by-s…

lieferbar ab 30.11.2026.

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Yue Song, Thomas Anderson Keller, Nicu Sebe, Max Welling
Structured Representation Learning

Synthesis Lectures on Computer Vision

This book introduces approaches to generalize the benefits of equivariant deep learning to a broader set of learned structures through learned homomorphisms. In the field of machine learning, the idea of …

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Roshan Srivastav, Purna C. Nayak
Applications of Machine Learning in Hydroclimatology

The Springer Series in Applied Machine Learning

Applications of Machine Learning in Hydroclimatology is a comprehensive exploration of the transformative potential of machine learning for addressing critical challenges in water resources management. Th…

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Predrag S. Stanimirovi¿, Yimin Wei, Shuai Li, Dimitrios Gerontitis
Generalized Matrix Inversion: A Machine Learning Approach

Background Information.- 2 Gradient Neural Network (GNN) and their Modifications.- 3 Zeroing Neural Network (ZNN).- 4 From iterations to ZNNs and vice versa, 5 Modified ZNN dynamical systems.

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Du¿an Stipanovi¿
Difference Equations and Machine Learning

This book presents in-depth explanations of well-known and recognized behaviors of neural networks in machine learning. In addition, the author provides novel technical analyses of behaviors of discrete-t…

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David Stroud
Advanced Large Language Model Operations

The Springer Series in Applied Machine Learning

This book presents a practitioner-oriented treatment of LLMOps: the engineering discipline required to deploy, scale, and govern large language model systems in production. Advanced Large Language Model O…

lieferbar in mind. 4 Wochen

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Changho Suh
Probability for Information Technology

This book introduces probabilistic modelling and explores its role in solving a broad spectrum of engineering problems that arise in Information Technology (IT). Divided into three parts, it begins by lay…

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Yi Sun, Rod Adams
A Mathematical Introduction to Data Science with Python

This textbook serves as a companion to "A Mathematical Introduction to Data Science". It uses Python programming to provide a comprehensive foundation in the mathematics needed for data science.…

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Jian-Qiao Sun
Random Vibration with Machine Learning Method

Nonlinear Physical Science

The book presents the theoretical foundation of random vibration of dynamic systems and new machine learning methods for the analysis of linear and nonlinear random vibration problems. This is the first b…

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Gaurav Suri, Jay McClelland
The Emergent Mind

As heard on BBC Radio 4 Start the Week A New Scientist Best Book of the Year A Next Big Ideas ClubBook of the Year'Excellent' - Geoffrey Hinton, the 'godfather of AI' and Nobel laureate in Physics 'An ind…

lieferbar in mind. 4 Wochen

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Gaurav Suri, Jay McClelland
The Emergent Mind

'Excellent' - Geoffrey Hinton, the 'godfather of AI' and Nobel laureate in Physics 'An indispensable guide to both ourselves and the coming age of AI' - Mustafa Suleyman, bestselling co-author of The Comi…

lieferbar ab 22.10.2026.

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Joe Suzuki
Graphical Models and Causal Discovery with Python

Beginning with a gentle introduction to causal discovery and the foundations of probability and statistics, this textbook is written in a highly pedagogical way. By uniting probability theory, statistical…

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Joe Suzuki
Graphical Models and Causal Discovery with R

Beginning with a gentle introduction to causal discovery and the foundations of probability and statistics, this textbook is written in a highly pedagogical way. By uniting probability theory, statistical…

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Gero Szepannek
Grundprinzipien des maschinellen Lernens

Was steckt hinter den Algorithmen der künstlichen Intelligenz?Künstliche Intelligenz und maschinelles Lernen halten zunehmend Einzug, in betrieblichen Anwendungen wie in der Forschung. Nicht alle Anwender…

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Xiaoming Tao, Yiping Duan, Zhijin Qin, Danlan Huang
Wireless Multimedia Computational Communications

Wireless Networks

This book discusses the evolving designs and applications of multimedia content delivery and focuses on computing-based methods. It offers readers an in-depth understanding of how computational resources …

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Matus Telgarsky, Miroslav Dudik, Robert E. Schapire
Astral Space

From three of today's top researchers in machine learning, a groundbreaking new theory for understanding convex minimization at infinityNumerous fields of study rely on methods for minimizing convex funct…

lieferbar ab 26.1.2027.

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Jakub M. Tomczak
Deep Generative Modeling

This first comprehensive book on models behind Generative AI has been thoroughly revised to cover all major classes of deep generative models: mixture models, Probabilistic Circuits, Autoregressive Models…

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