Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization - Image 1

£125.00

CRC Press Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization

Name: Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization
Brand: CRC Press
Price: 125.0 GBP
Availability: InStock

Econometrics

Price History & Forecast

Last 35 days • 35 data points (No recent data available)

Historical

Generating forecast...

Price Distribution

Price distribution over 35 days • 2 price levels

Days at Price

Current Price

Price Analysis

Most common price: £125 (26 days, 74.3%)

Price range: £125 - £153

Price levels: 2 different prices over 35 days

Description

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization describes such algorithms as Locally Linear Embedding (LLE), Laplacian Eigenmaps, Isomap, Semidefinite Embedding, and t-SNE to resolve the problem of dimensionality reduction in the case of non-linear relationships within the data. Underlying mathematical concepts, derivations, and proofs with logical explanations for these algorithms are discussed, including strengths and limitations. The book highlights important use cases of these algorithms and provides examples along with visualizations. Comparative study of the algorithms is presented to give a clear idea on selecting the best suitable algorithm for a given dataset for efficient dimensionality reduction and data visualization. FEATURES Demonstrates how unsupervised learning approaches can be used for dimensionality reduction Neatly explains algorithms with a focus on the fundamentals and underlying mathematical concepts Describes the comparative study of the algorithms and discusses when and where each algorithm is best suitable for use Provides use cases, illustrative examples, and visualizations of each algorithm Helps visualize and create compact representations of high dimensional and intricate data for various real-world applications and data analysis This book is aimed at professionals, graduate students, and researchers in Computer Science and Engineering, Data Science, Machine Learning, Computer Vision, Data Mining, Deep Learning, Sensor Data Filtering, Feature Extraction for Control Systems, and Medical Instruments Input Extraction.

Product Specifications

Brand: CRC Press
Format: hardcover
ASIN: 1032041013
Category: Books > Subjects > Business, Finance & Law > Economics > Econometrics
Domain: Amazon UK
Release Date: 02 September 2021
Listed Since: 18 March 2021

Barcode

No barcode data available

CRC Press Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization

Price History & Forecast

Price Distribution

Price Analysis

Description

Product Specifications

Barcode

Similar Products You Might Like

Elements of Dimensionality Reduction and Manifold Learning

Nonlinear Dimensionality Reduction Techniques: A Data Structure Preservation Approach

Unsupervised Learning: A Dynamic Approach (IEEE Press Series on Computational Intelligence)

CRC Press Manifold Learning Theory and Applications Book

Dimensionality Reduction in Data Science

Multilinear Subspace Learning: Dimensionality Reduction of Multidimensional Data (Chapman & Hall/CRC Machine Learning & Pattern Recognition)

Fundamentals and Methods of Machine and Deep Learning: Algorithms, Tools, and Applications

Nonlinear Dimensionality Reduction Techniques: A Data Structure Preservation Approach

Statistical Learning and Data Science (Computer Science and Data Analysis)

Data Visualization with Category Theory and Geometry: With a Critical Analysis and Refinement of UMAP: 3 (Mathematics of Data, 3)

Statistical Learning and Data Science (Chapman & Hall/CRC Computer Science & Data Analysis)

Data Without Labels: Practical Unsupervised Machine Learning

Springer Feature Learning and Understanding Algorithms Book

Machine Learning and Big Data: Concepts, Algorithms, Tools and Applications

Learning Representation for Multi-View Data Analysis: Models and Applications (Advanced Information and Knowledge Processing)

CRC Press Applied Machine Learning for Smart Data Analysis Book

Sufficient Dimension Reduction: Methods and Applications with R (Chapman & Hall/CRC Monographs on Statistics and Applied Probability)

Sampling Techniques for Supervised or Unsupervised Tasks (Unsupervised and Semi-Supervised Learning)

Springer - Unsupervised Feature Extraction in Bioinformatics

Linear Algebra and Optimization for Machine Learning: A Textbook

Machine Learning: Theory and Practice

Computational Analysis and Deep Learning for Medical Care: Principles, Methods, and Applications

Tensor Networks for Dimensionality Reduction and Large-scale Optimization: Part 1 Low-Rank Tensor Decompositions (Foundations and Trends (R) in Machine Learning)

Data Mining for Bioinformatics