Processing ......
FreeComputerBooks.com
Links to Free Computer, Mathematics, Technical Books all over the World
 
Data Compression Explained
🌠 Top Free Machine Learning Books - 100% Free or Open Source!
  • Title Data Compression Explained
  • Author(s) Matt Mahoney
  • Publisher: Dell, Inc.
  • Paperback: N/A
  • eBook HTML, ePub, Mobi
  • Language: English
  • ISBN-10/ASIN: N/A
  • ISBN-13: N/A
  • Share This:  

Book Description

Data Compression is the art of reducing the number of bits needed to store or transmit data. Prior programming ability and some math skills will be needed.

This book provides an extensive introduction to the theory underlying today's compression techniques with detailed instruction for their applications using several examples to explain the concepts. Encompassing the entire field of data compression, it includes lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, scalar and vector quantization.

It also provides a working knowledge of data compression, giving the reader the tools to develop a complete and concise compression package upon completion of the book.

About the Authors
  • N/A
Reviews, Ratings, and Recommendations: Related Book Categories: Read and Download Links: Similar Books:
  • Data Compression: The Complete Refrence (David Salomon)

    A comprehensive reference for the many types of Data Compression, including extensive coverage of audio and video compression, geometric compression and the edgebreaker method, and information about archiving data.

  • Data Spaces: Design, Deployment and Future Directions

    This open access book aims to educate Data Space designers to understand what is required to create a successful data space. It arranges these contributions into three parts: design, deployment, and future directions respectively.

  • Building the Data Lakehouse (Bill Inmon, et al.)

    Learn about the features and architecture of the data lakehouse, along with its powerful analytical infrastructure. The data lakehouse is the next generation of the data warehouse and data lake.

  • Data Hub Guide for Architects (Ken Krupa, et al.)

    What is a data hub? How does it simplify data integration? A data hub is a data store that acts as the central hub in a hub-andspoke architecture, and is powered by a multi-model database.

  • Making Sense of Stream Processing: Behind Apache Kafka

    This book shows you how stream processing can make your data storage and processing systems more flexible and less complex. It explains how these projects can help you reorient your database architecture around streams and materialized views.

  • Introduction to Storage Area Networks (Jon Tate, et al)

    This book provides an introduction to SAN and Ethernet networking, and how these networks help to achieve a smarter data center. This book is intended for people who are not very familiar with IT, or who are just starting out in the IT world.

  • Understanding Machine Learning: From Theory to Algorithms

    Explains the principles behind the automated learning approach and the considerations underlying its usage. Provides an extensive theoretical account of the fundamental ideas underlying machine learning and the mathematical derivations.

  • Foundations of Machine Learning (Mehryar Mohri, et al)

    This book is a general introduction to machine learning. It covers fundamental modern topics in machine learning while providing the theoretical basis and conceptual tools needed for the discussion and justification of algorithms.

  • Machine Learning Yearning (Andrew Ng)

    You will learn how to align on ML strategies in a team setting, as well as how to set up development (dev) sets and test sets. After finishing this book, you will have a deep understanding of how to set technical direction for a machine learning project.

Book Categories
:
Other Categories
Resources and Links