Hallo! Tracked shipping to Netherlands with Delivery Duty Paid for just €7 

Ship to
Netherlands
0

My Account

  • argentina
  • chile
  • colombia
  • españa
  • méxico
  • perú
  • estados unidos
  • internacional

menu

Select your country

Americas

Europe

Rest of the world

portada Reverse Hypothesis Machine Learning: A Practitioner's Perspective (Intelligent Systems Reference Library)
Type
Physical Book
Publisher
Author
Year
2018
Language
English
Pages
138
Format
Paperback
ISBN13
9783319856261
Categories

Reverse Hypothesis Machine Learning: A Practitioner's Perspective (Intelligent Systems Reference Library)

Parag Kulkarni (Author) · Springer · Paperback

Reverse Hypothesis Machine Learning: A Practitioner's Perspective (Intelligent Systems Reference Library) - Parag Kulkarni

Cheaper New Book Imported to Netherlands
Delivery: 10 Sep - 17 Sep Shipping: 12 to 16 business days.
€ 115,10
Faster New Book Imported to Netherlands
Delivery: 28 Aug - 02 Sep Shipping: 4 to 5 business days.
€ 164,25
Import costs and 9% BTW included in the price ✅
€ 115,10

Choose the list to add your product or create one New List

Go to My Wishlists
Calculate shipping cost

Synopsis "Reverse Hypothesis Machine Learning: A Practitioner's Perspective (Intelligent Systems Reference Library) "

This book introduces a paradigm of reverse hypothesis machines (RHM), focusing on knowledge innovation and machine learning. Knowledge- acquisition -based learning is constrained by large volumes of data and is time consuming. Hence Knowledge innovation based learning is the need of time. Since under-learning results in cognitive inabilities and over-learning compromises freedom, there is need for optimal machine learning. All existing learning techniques rely on mapping input and output and establishing mathematical relationships between them. Though methods change the paradigm remains the same-the forward hypothesis machine paradigm, which tries to minimize uncertainty. The RHM, on the other hand, makes use of uncertainty for creative learning. The approach uses limited data to help identify new and surprising solutions. It focuses on improving learnability, unlike traditional approaches, which focus on accuracy. The book is useful as a reference book for machine learning researchers and professionals as well as machine intelligence enthusiasts. It can also used by practitioners to develop new machine learning applications to solve problems that require creativity.

Customers reviews

More customer reviews
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)
  • 0% (0)

Frequently Asked Questions about the Book

Is the book original?

All books in our catalog are Original.

In what language is the book written?

The book is written in English.

What is the format of this book?

The binding of this edition is Paperback.

Questions and Answers about the Book

Do you have a question about the book? Login to be able to add your own question.

Opinions about Bookdelivery

More customer reviews