Active Learning - Burr Settles
-25% koodilla BOOKS
Toimitus 12-18 arkipäivässä
30 päivän palautusoikeus
The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose "queries," usually in the form of unlabeled data instances to be labeled by an "oracle" (e.g., a human annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many ... Täydellinen kuvaus
Saatat myös pitää
TOP
Six Not-so-easy Pieces: Einstein's Relativity, Symmetry, and Space-Time
Richard P. Feynman, Robert B. Leighton, Matthew Sands
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Six Easy Pieces: Essentials of Physics Explained by Its Most Brilliant Teacher
Richard P. Feynman, Robert B. Leighton, Matthew Sands
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Behave: The Biology of Humans at Our Best and Worst
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Determined: The Science of Life Without Free Will
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
The Age of Alchemy: How Early Innovators Shaped Modern Chemistry
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
The Secrets of our DNA: How Genetics has Changed the World
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Why We Sleep: Unlocking the Power of Sleep and Dreams
-25% koodilla BOOKS
Varastossa
TOP
Biology: A Global Approach, Global Edition
Neil Campbell, Rebecca Orr, Lisa Urry, Peter Minorsky, Michael Cain, Jane Reece, Steven Wasserman
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Why Machines Learn: The Elegant Maths Behind Modern AI
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
A Short History of Nearly Everything 2.0
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Astrophysics for People in a Hurry: Essays on the Universe and Our Place Within It
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
The Rise and Fall of the Dinosaurs: A New History of a Lost World
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
The Rise and Reign of the Mammals: A New History, from the Shadow of the Dinosaurs to Us
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Learn Faster, Perform Better: A Musician's Guide to the Neuroscience of Practicing
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Beyond Inheritance: Our Ever-Mutating Cells and a New Understanding of Health
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
A Brief History of Time: From the Big Bang to Black Holes
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Thing Explainer: Complicated Stuff in Simple Words
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Introduction to Quantum Mechanics
Darrell F. Schroeter, David J. Griffiths
-25% koodilla BOOKS
Toimittajalla varastossa
TOP
Universe: The Definitive Visual Guide
-25% koodilla BOOKS
Toimittajalla varastossa
Kuvaus
The key idea behind active learning is that a machine learning algorithm can perform better with less training if it is allowed to choose the data from which it learns. An active learner may pose "queries," usually in the form of unlabeled data instances to be labeled by an "oracle" (e.g., a human annotator) that already understands the nature of the problem. This sort of approach is well-motivated in many modern machine learning and data mining applications, where unlabeled data may be abundant or easy to come by, but training labels are difficult, time-consuming, or expensive to obtain. This book is a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organized into four broad categories, or "query selection frameworks." We also touch on some of the theoretical foundations of active learning, and conclude with an overview of the strengths and weaknesses of these approaches in practice, including a summary of ongoing work to address these open challenges and opportunities. Table of Contents: Automating Inquiry / Uncertainty Sampling / Searching Through the Hypothesis Space / Minimizing Expected Error and Variance / Exploiting Structure in Data / Theory / Practical Considerations
Lisätietoja
| Kirjoittaja | Burr Settles |
|---|---|
| Julkaisija | Springer Nature Switzerland |
| Series | Synthesis Lectures on Artificial Intelligence and Machine Learning |
| Julkaisuvuosi | 2012 |
| Kannen tyyppi | Pehmeäkantinen |
| EAN | 9783031004322 |