Ergebnisse für: Elements Statistical Learning

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Buch Cover The Elements of Statistical Learning
The Elements of Statistical Learning
Trevor Hastie, Robert Tibshirani, Jerome Friedman
Springer US
85.59 € · Hardcover
Averaging Boosting Projection pursuit Random Forest Support Vector Machine classification clustering data mining machine learning supervised learning unsupervised learning
This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphi...
Buch Cover The Elements of Statistical Learning
The Elements of Statistical Learning
Trevor Hastie, Robert Tibshirani, Jerome Friedman
Springer US
85.59 € · Hardcover
Boosting Random Forest Support Vector Machine algorithms bioinformatics classification clustering data mining ensemble method learning machine learning neural networks statistics supervised learning unsupervised learning
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the fiel...
Buch Cover Elements of Dimensionality Reduction and Manifold Learning
Elements of Dimensionality Reduction and Manifold Learning
Benyamin Ghojogh, Mark Crowley, Fakhri Karray, Ali Ghodsi
Springer International Publishing
106.99 € · Hardcover
Data Reduction Data Visualization Dimensionality Reduction Feature Extraction Machine Learning Manifold Learning Pattern Analysis Representation Learning Subspace Learning Unsupervised Learning artificial neural networks deep learning data embedding data science statistical learning
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of linear and nonlinear dimensionality reduction and mani...
Buch Cover Unsupervised Learning Algorithms
Unsupervised Learning Algorithms

Springer International Publishing
117.69 € · Hardcover
Big Data Patterns Data Analytics Data Mining Elements Statistical Learning Genomic Data Sets Machine Learning Pattern Recognition Statistical Learning Theory Unsupervised Algorithms Unsupervised Learning
This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity a...
Buch Cover The Elements of Statistical Learning
The Elements of Statistical Learning
Trevor Hastie, Robert Tibshirani, Jerome Friedman
Springer US
85.59 € · eBook
Averaging Boosting Projection pursuit Random Forest Support Vector Machine classification clustering data mining machine learning supervised learning unsupervised learning
This book describes the important ideas in a variety of fields such as medicine, biology, finance, and marketing in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of colour graphi...
Buch Cover The Elements of Statistical Learning
The Elements of Statistical Learning
Trevor Hastie, Robert Tibshirani, Jerome Friedman
Springer US
85.59 € · eBook
Boosting Random Forest Support Vector Machine algorithms bioinformatics classification clustering data mining ensemble method learning machine learning neural networks statistics supervised learning unsupervised learning
During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the fiel...
Buch Cover Statistical Learning with Math and Python
Statistical Learning with Math and Python
Joe Suzuki
Springer Singapore
40.65 € · Paperback
Machine Learning Statistical Learning Artificial Intelligence Data Mining Unsupervised Learning Linear Regression Resampling Information Criteria Support Vector Machine Elements of Statistical Learning Introduction to Statistical Learning Python
The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of machine learning and data science by considering math problems and building Python programs. As the prelimina...
Buch Cover Statistical Learning with Math and Python
Statistical Learning with Math and Python
Joe Suzuki
Springer Singapore
39.58 € · eBook
Machine Learning Statistical Learning Artificial Intelligence Data Mining Unsupervised Learning Linear Regression Resampling Information Criteria Support Vector Machine Elements of Statistical Learning Introduction to Statistical Learning Python
The most crucial ability for machine learning and data science is mathematical logic for grasping their essence rather than knowledge and experience. This textbook approaches the essence of machine learning and data science by considering math problems and building Python programs. As the prelimina...
Buch Cover Elements of Dimensionality Reduction and Manifold Learning
Elements of Dimensionality Reduction and Manifold Learning
Benyamin Ghojogh, Mark Crowley, Fakhri Karray, Ali Ghodsi
Springer International Publishing
74.89 € · Paperback
Data Reduction Data Visualization Dimensionality Reduction Feature Extraction Machine Learning Manifold Learning Pattern Analysis Representation Learning Subspace Learning Unsupervised Learning artificial neural networks deep learning data embedding data science statistical learning
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of linear and nonlinear dimensionality reduction and mani...
Buch Cover Elements of Dimensionality Reduction and Manifold Learning
Elements of Dimensionality Reduction and Manifold Learning
Benyamin Ghojogh, Mark Crowley, Fakhri Karray, Ali Ghodsi
Springer International Publishing
74.89 € · eBook
Data Reduction Data Visualization Dimensionality Reduction Feature Extraction Machine Learning Manifold Learning Pattern Analysis Representation Learning Subspace Learning Unsupervised Learning artificial neural networks deep learning data embedding data science statistical learning
Dimensionality reduction, also known as manifold learning, is an area of machine learning used for extracting informative features from data for better representation of data or separation between classes. This book presents a cohesive review of linear and nonlinear dimensionality reduction and mani...
Buch Cover Unsupervised Learning Algorithms
Unsupervised Learning Algorithms

Springer International Publishing
117.69 € · Paperback
Big Data Patterns Data Analytics Data Mining Elements Statistical Learning Genomic Data Sets Machine Learning Pattern Recognition Statistical Learning Theory Unsupervised Algorithms Unsupervised Learning
This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity a...
Buch Cover Unsupervised Learning Algorithms
Unsupervised Learning Algorithms

Springer International Publishing
106.99 € · eBook
Big Data Patterns Data Analytics Data Mining Elements Statistical Learning Genomic Data Sets Machine Learning Pattern Recognition Statistical Learning Theory Unsupervised Algorithms Unsupervised Learning
This book summarizes the state-of-the-art in unsupervised learning. The contributors discuss how with the proliferation of massive amounts of unlabeled data, unsupervised learning algorithms, which can automatically discover interesting and useful patterns in such data, have gained popularity a...
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