Lyssna när som helst, var som helst

Kliv in i en oändlig värld av stories

  • 1 miljon stories
  • Hundratals nya stories varje vecka
  • Få tillgång till exklusivt innehåll
  • Avsluta när du vill
Starta erbjudandet
SE - Details page - Device banner - 894x1036

Hands-On One-shot Learning with Python: Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch

Språk
Engelska
Format
Kategori

Fakta

Get to grips with building powerful deep learning models using PyTorch and scikit-learn

Key Features

• Learn how you can speed up the deep learning process with one-shot learning

• Use Python and PyTorch to build state-of-the-art one-shot learning models

• Explore architectures such as Siamese networks, memory-augmented neural networks, model-agnostic meta-learning, and discriminative k-shot learning

Book Description

One-shot learning has been an active field of research for scientists trying to develop a cognitive machine that mimics human learning. With this book, you'll explore key approaches to one-shot learning, such as metrics-based, model-based, and optimization-based techniques, all with the help of practical examples.

Hands-On One-shot Learning with Python will guide you through the exploration and design of deep learning models that can obtain information about an object from one or just a few training samples. The book begins with an overview of deep learning and one-shot learning and then introduces you to the different methods you can use to achieve it, such as deep learning architectures and probabilistic models. Once you've got to grips with the core principles, you'll explore real-world examples and implementations of one-shot learning using PyTorch 1.x on datasets such as Omniglot and MiniImageNet. Finally, you'll explore generative modeling-based methods and discover the key considerations for building systems that exhibit human-level intelligence.

By the end of this book, you'll be well-versed with the different one- and few-shot learning methods and be able to use them to build your own deep learning models.

What you will learn

• Get to grips with the fundamental concepts of one- and few-shot learning

• Work with different deep learning architectures for one-shot learning

• Understand when to use one-shot and transfer learning, respectively

• Study the Bayesian network approach for one-shot learning

• Implement one-shot learning approaches based on metrics, models, and optimization in PyTorch

• Discover different optimization algorithms that help to improve accuracy even with smaller volumes of data

• Explore various one-shot learning architectures based on classification and regression

Who this book is for

If you're an AI researcher or a machine learning or deep learning expert looking to explore one-shot learning, this book is for you. It will help you get started with implementing various one-shot techniques to train models faster. Some Python programming experience is necessary to understand the concepts covered in this book.

© 2020 Packt Publishing (E-bok): 9781838824877

Utgivningsdatum

E-bok: 10 april 2020

Andra gillade också ...

  1. Deep Learning: Guide to Machine Learning and Artificial Intelligence David Feldspar
  2. Everyday Calculus: Discovering the Hidden Math All around Us Oscar E. Fernandez
  3. Machine Learning: Deep Learning, Text Analytics, and Reinforcement Learning with Big Data David Feldspar
  4. Artificial Intelligence For Dummies Luca Massaron
  5. Hands-on ML Projects with OpenCV Mugesh S.
  6. The Upside of Irrationality: The Unexpected Benefits of Defying Logic at Work and at Home Dan Ariely
  7. Machine Learning in Python: Hands on Machine Learning with Python Tools, Concepts and Techniques Bob Mather
  8. Blockchain For Dummies Tiana Laurence
  9. The Creativity Code: How AI is learning to write, paint and think Marcus du Sautoy
  10. MACHINE LEARNING AND ARTIFICIAL INTELLIGENCE: A Comprehensive Guide to Understanding and Implementing ML and AI (2023 Beginner Crash Course) Carl Dennis
  11. Reinforcement Learning: Machine Learning, Gamma, and Inventory Management David Feldspar
  12. Machine Learning Introbooks Team
  13. Numbers: A Very Short Introduction Peter M. Higgins
  14. What We Cannot Know: Explorations at the Edge of Knowledge Marcus du Sautoy
  15. AI for beginners: Begin your AI developer journey in 2024 Et Tu Code
  16. Artificial Intelligence with Python for Beginners: Comprehensive Guide to Building AI Applications James Ferry
  17. Human Universe Professor Brian Cox
  18. Standard Deviations: Flawed Assumptions, Tortured Data, and Other Ways to Lie with Statistics Gary Smith
  19. Deep Learning for Finance: Creating Machine & Deep Learning Models for Trading in Python Sofien Kaabar
  20. Nudge: Improving Decisions About Health, Wealth, and Happiness Richard H. Thaler
  21. Introducing Python: Modern Computing in Simple Packages, 2nd Edition Bill Lubanovic
  22. Artificial Intelligence For Dummies, 3rd Edition Luca Massaron
  23. Python Essentials For Dummies Alan Simpson
  24. Anger Management for Dummies: 2nd Edition Charles H. Elliott, PhD
  25. Basic Python in Finance: How to Implement Financial Trading Strategies and Analysis using Python Bob Mather
  26. Coders: Who They Are, What They Think and How They Are Changing Our World Clive Thompson
  27. Quantum Electronics Introbooks Team
  28. The World According to Physics Jim Al-Khalili
  29. Critical Thinking Skills For Dummies Martin Cohen
  30. Dedicated: The Case for Commitment in an Age of Infinite Browsing Pete Davis
  31. Mastering OpenCV with Python Ayush Vaishya
  32. The Universe Andrew Cohen
  33. Innate: How the Wiring of Our Brains Shapes Who We Are Kevin J. Mitchell
  34. The Moral Landscape: How Science Can Determine Human Values Sam Harris
  35. The Pleasure of Finding Things Out: The Best Short Works of Richard P. Feynman Richard P. Feynman
  36. Focus: The Hidden Driver of Excellence Daniel Goleman
  37. Thinking: The New Science of Decision-Making, Problem-Solving, and Prediction John Brockman
  38. The Origins of Everything in 100 Pages (More or Less) David Bercovici
  39. The Quantum Moment: How Planck, Bohr, Einstein, and Heisenberg Taught Us to Love Uncertainty Alfred Scharff Goldhaber
  40. Data Science For Dummies: 2nd Edition Lillian Pierson
  41. Gravity’s Century: From Einstein’s Eclipse to Images of Black Holes Ron Cowen
  42. The Universe in Your Hand: A Journey Through Space, Time and Beyond Christophe Galfard
  43. Predictably Irrational: The Hidden Forces that Shape Our Decisions Dan Ariely
  44. Think Like a Monk: Train Your Mind for Peace and Purpose Every Day Jay Shetty
  45. Scientific Methods Introbooks Team

Därför kommer du älska Storytel:

  • 1 miljon stories

  • Lyssna och läs offline

  • Exklusiva nyheter varje vecka

  • Kids Mode (barnsäker miljö)

Populäraste valet

Premium

Lyssna och läs ofta.

169 kr /månad
  • 1 konto

  • 100 timmar/månad

  • Exklusivt innehåll varje vecka

  • Avsluta när du vill

  • Obegränsad lyssning på podcasts

Starta erbjudandet

Unlimited

Lyssna och läs obegränsat.

229 kr /månad
  • 1 konto

  • Lyssna obegränsat

  • Exklusivt innehåll varje vecka

  • Avsluta när du vill

  • Obegränsad lyssning på podcasts

Starta erbjudandet

Family

Dela stories med hela familjen.

Från 239 kr/månad
  • 2-6 konton

  • 100 timmar/månad för varje konto

  • Exklusivt innehåll varje vecka

  • Avsluta när du vill

  • Obegränsad lyssning på podcasts

2 konton

239 kr /månad
Starta erbjudandet

Flex

Lyssna och läs ibland – spara dina olyssnade timmar.

99 kr /månad
  • 1 konto

  • 20 timmar/månad

  • Spara upp till 100 olyssnade timmar

  • Exklusivt innehåll varje vecka

  • Avsluta när du vill

  • Obegränsad lyssning på podcasts

Starta erbjudandet