Ergebnisse für: Machine Learning
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This book is designed to provide a well-structured, comprehensive, and practical textbook on machine learning for undergraduate and graduate students in related fields. Through clear and accessible explanations, this book allows readers go master the concepts and techniques of machine learning, equi...
Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research. This textbook offers a comprehensive and unbiased introduction to almost all aspects of machine learning, from...
Machine learning (ML) has become a commonplace element in our everyday lives and a standard tool for many fields of science and engineering. To make optimal use of ML, it is essential to understand its underlying principles. This book approaches ML as the computational implementation ...
Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines. However, unlike previous books that only discuss these rather different approaches in isolation, it ...
The ability to learn is one of the most fundamental attributes of intelligent behavior. Consequently, progress in the theory and computer modeling of learn ing processes is of great significance to fields concerned with understanding in telligence. Such fields include cognitive science, artificial i...
Machine Learning - Modeling Data Locally and Globally presents a novel and unified theory that tries to seamlessly integrate different algorithms. Specifically, the book distinguishes the inner nature of machine learning algorithms as either "local learning"or "global learning."This theory not only ...
One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance...
Der kompakte Schnelleinstieg in Machine Learning und Deep Learning
Die 3. Auflage des Bestsellers wurde ergänzt durch Kapitel zu Large Language Models wie ChatGPT und zu MLOps
Anhand konkreter Datensätze lernst du einen typischen Workflow ke...
Aktualisierte und erweiterte 3. Auflage des Bestsellers zu TensorFlow und Deep Learning
Behandelt jetzt viele neue Features von Scikit-Learn sowie die Keras-Tuner-Bibliothek und die NLP-Bibliothek Transformers von Hugging Face
Führt Sie metho...
Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines. However, unlike previous books that only discuss these rather different approaches in isolation, it ...
Machine Learning: Discriminative and Generative covers the main contemporary themes and tools in machine learning ranging from Bayesian probabilistic models to discriminative support-vector machines. However, unlike previous books that only discuss these rather different approaches in isolation, it ...
Machine Learning, a vital and core area of artificial intelligence (AI), is propelling the AI field ever further and making it one of the most compelling areas of computer science research. This textbook offers a comprehensive and unbiased introduction to almost all aspects of machine learning, from...
Dig deep into the data with a hands-on guide to machinelearning
Machine Learning: Hands-On for Developers and TechnicalProfessionals provides hands-on instruction and fully-codedworking examples for the most common machine learning techniquesused by developers and technical professionals. The book c...
Dieses Buch richtet sich an alle, welche die enormen Potenziale maschinellen Lernens für wissenschaftliche Fragestellungen und innovative Ansätze in Studium oder Beruf nutzen möchten. Denn maschinelles Lernen eröffnet neue Möglichkeiten zum effizienten Umgang mit umfassenden, komplex strukturie...
One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance...
Dig deep into the data with a hands-on guide to machine learning
Machine Learning: Hands-On for Developers and Technical Professionals provides hands-on instruction and fully-coded working examples for the most common machine learning techniques used by developers and technical professionals. The bo...
One of the currently most active research areas within Artificial Intelligence is the field of Machine Learning. which involves the study and development of computational models of learning processes. A major goal of research in this field is to build computers capable of improving their performance...
Dig deep into the data with a hands-on guide to machinelearning
Machine Learning: Hands-On for Developers and TechnicalProfessionals provides hands-on instruction and fully-codedworking examples for the most common machine learning techniquesused by developers and technical professionals. The book c...
The ability to learn is one of the most fundamental attributes of intelligent behavior. Consequently, progress in the theory and computer modeling of learn ing processes is of great significance to fields concerned with understanding in telligence. Such fields include cognitive science, artificial i...
Machine learning (ML) has become a commonplace element in our everyday lives and a standard tool for many fields of science and engineering. To make optimal use of ML, it is essential to understand its underlying principles. This book approaches ML as the computational implementation ...