How Long to Read Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization

How Long Does it Take to Read Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization?

It takes the average reader 2 hours and 56 minutes to read Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization by B.K. Tripathy

Assuming a reading speed of 250 words per minute. Learn more

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.

How long is Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization?

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization by B.K. Tripathy is 174 pages long, and a total of 44,196 words.

This makes it 59% the length of the average book. It also has 54% more words than the average book.

How Long Does it Take to Read Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization Aloud?

The average oral reading speed is 183 words per minute. This means it takes 4 hours and 1 minute to read Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization aloud.

What Reading Level is Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization?

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization is suitable for students ages 10 and up.

Note that there may be other factors that effect this rating besides length that are not factored in on this page. This may include things like complex language or sensitive topics not suitable for students of certain ages.

When deciding what to show young students always use your best judgement and consult a professional.

Where Can I Buy Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization?

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization by B.K. Tripathy is sold by several retailers and bookshops. However, Read Time works with Amazon to provide an easier way to purchase books.

To buy Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization by B.K. Tripathy on Amazon click the button below.