Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Free Learning

Hands-On One-shot Learning with Python

You're reading from Hands-On One-shot Learning with Python Learn to implement fast and accurate deep learning models with fewer training samples using PyTorch

Product type Paperback

Published in Apr 2020

Publisher Packt

ISBN-13 9781838825461

Length 156 pages

Edition 1st Edition

Languages

Python

Tools

PyTorch

Concepts

Deep Learning

Authors (2):

Ankush Garg

Shruti Jadon

View More author details

Table of Contents (11) Chapters

Preface

1. Section 1: One-shot Learning Introduction

2. Introduction to One-shot Learning FREE CHAPTER

3. Section 2: Deep Learning Architectures

4. Metrics-Based Methods

5. Model-Based Methods

6. Optimization-Based Methods

7. Section 3: Other Methods and Conclusion

8. Generative Modeling-Based Methods

9. Conclusions and Other Approaches

10. Other Books You May Enjoy

Leave a review - let other readers know what you think

Technical requirements

The following libraries will be required to learn and execute the project in this chapter:

Python
Anaconda
Jupyter Notebook
PyTorch
Matplotlib
scikit-learn

You can find the code file for the chapter in the GitHub repo of the book, at https://github.com/PacktPublishing/Hands-On-One-shot-Learning-with-Python.

The rest of the chapter is locked

Register for a free Packt account to unlock a world of extra content!

A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.

Unlock this book and the full library FREE for 7 days

Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of

Start free trial

Renews at $19.99/month. Cancel anytime

Authors (2)

Jadon

Jadon

Shruti Jadon is currently working as a Machine Learning Software Engineer at Juniper Networks, Sunnyvale and visiting Researcher at Rhode Island Hospital (Brown University). She has obtained her master's degree in Computer Science from University of Massachusetts, Amherst. Her research interests include deep learning architectures, computer vision, and convex optimization. In the past, she has worked at Autodesk, Quantiphi, SAP Labs, and Snapdeal.

See other products by Jadon

Garg

Garg

Ankush Garg is currently working as a Software Engineer in the auto-translation team at Google, Mountain View. He has obtained his master's degree in Computer Science from the University of Massachusetts, Amherst and Bachelor's at NSIT, Delhi. His research interests include language modeling, model compression, and optimization. In the past, he has worked as a Software Engineer at Amazon, India.

See other products by Garg

Other recommended products

Related to this chapter

Hands-On Meta Learning with Python

Hands-On Meta Learning with Python

This hands-on guide for meta learning starts with exploring the principles, algorithms, and implementations of Meta learning with Tensorflow, Keras, and Python. Once it sets the foundation of "learning to learn", the book will help you implement your meta learning algorithms from scratch.

Dec 2018 7h 32m

Hands-On Mathematics for Deep Learning

Hands-On Mathematics for Deep Learning

The main aim of this book is to make the advanced mathematical background accessible to someone with a programming background. This book will equip the readers with not only deep learning architectures but the mathematics behind them. With this book, you will understand the relevant mathematics that goes behind building deep learning models.

Jun 2020 12h 8m

Advanced Deep Learning with Python

Advanced Deep Learning with Python

This book is an expert-level guide to master the neural network variants using the Python ecosystem. You will gain the skills to build smarter, faster, and efficient deep learning systems with practical examples. By the end of this book, you will be up to date with the latest advances and current researches in the deep learning domain.

Dec 2019 15h 36m

Hands-On Java Deep Learning for Computer Vision

Hands-On Java Deep Learning for Computer Vision

This book will take you through the process of efficiently training deep neural networks in Java for Computer Vision-related tasks. You will build real-world applications ranging from simple Java handwritten digit recognition models to real-time autonomous car driving systems and face recognition models using the popular Java-based libraries.

Feb 2019 8h 40m

Hands-On Deep Learning Algorithms with Python

Hands-On Deep Learning Algorithms with Python

This book introduces basic-to-advanced deep learning algorithms used in a production environment by AI researchers and principal data scientists; it explains algorithms intuitively, including the underlying math, and shows how to implement them using popular Python-based deep learning libraries such as TensorFlow.

Jul 2019 17h 4m

Neural Network Projects with Python

Neural Network Projects with Python

This book contains practical implementations of several deep learning projects in multiple domains, including in regression-based tasks such as taxi fare prediction in New York City, image classification of cats and dogs using a convolutional neural network, implementing a facial recognition security system using Siamese Neural Networks, and more.

Feb 2019 10h 16m

Mobile Artificial Intelligence Projects

Mobile Artificial Intelligence Projects

Artificial intelligence (AI) is rapidly becoming the most popular topic in business and science. This book introduces AI concepts and their use cases with a hands-on and application-focused approach. We will cover a range of projects covering tasks such as automated reasoning, facial recognition, digital assistants, auto text generation, and more.

Mar 2019 10h 24m

Applied Deep Learning with PyTorch

Applied Deep Learning with PyTorch

Starting with the basics of deep learning and their various applications, Applied Deep Learning with PyTorch shows you how to solve trending tasks, such as image classification and natural language processing by understanding the different architectures of the neural networks.

Apr 2019 8h 28m

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

Starting from the basics of neural networks, this book covers over 50 applications of computer vision and helps you to gain a solid understanding of the theory of various architectures before implementing them. Each use case is accompanied by a notebook in GitHub with ready-to-execute code and self-assessment questions.

Nov 2020 27h 28m

Advanced Natural Language Processing with TensorFlow 2

Advanced Natural Language Processing with TensorFlow 2

This book provides hands-on training in NLP tools and techniques with intrinsic details. Apart from gaining expertise, you will be able to carry out novel state-of-the-art research using the skills gained.

Feb 2021 12h 40m

The Deep Learning with PyTorch Workshop

The Deep Learning with PyTorch Workshop

With this hands-on, self-paced guide, you'll explore crucial deep learning topics and discover the structure and syntax of PyTorch. Challenging activities and interactive exercises will keep you motivated and encourage you to build intelligent applications effectively.

Jul 2020 11h 0m

Deep Learning for Computer Vision

Deep Learning for Computer Vision

Deep learning has shown its power in several application areas of Artificial Intelligence, especially in Computer Vision, the science of manipulating and processing images. In this book, you will learn different techniques in deep learning to accomplish tasks related to object classification, object detection, image segmentation, captioning, image generation, and more. You will also explore their application using the popular Python libraries such as TensorFlow and Keras. With practical examples, you will learn to develop Computer Vision applications by leveraging the power of deep learning.

Jan 2018 10h 20m

Personalised recommendations for you

Based on your interests and search pattern

Modern Computer Vision with PyTorch

Modern Computer Vision with PyTorch

This book provides a hands-on approach to solving over 30 prominent real-world computer vision problems using PyTorch 2.x on actual datasets. Here you'll learn to build a neural network from scratch and optimize hyperparameters, perform image classification, multi-object detection, segmentation, and more. You'll also explore facial expression manipulation and combining CV with NLP and RL techniques, build generative AI applications, and take your model to production on AWS. By the end of this book, you'll master modern NN architectures and confidently solve real-world CV problems.

Jun 2024 24h 52m

Data Governance Handbook

Data Governance Handbook

This book provides a highly focused view of real business outcomes powered by data governance, that resonate with non-data executives such as CFOs and CEOs. You'll also find useful insights into how to implement data governance initiatives.

May 2024 13h 8m

Data Engineering with Databricks Cookbook

Data Engineering with Databricks Cookbook

This book shows you how to use Apache Spark, Delta Lake, and Databricks to build data pipelines, manage and transform data, optimize performance, and more. Additionally, you'll implement DataOps and DevOps practices, and orchestrate data workflows.

May 2024 14h 36m

Azure Data Engineer Associate Certification Guide

Azure Data Engineer Associate Certification Guide

Unlock the power of Azure data engineering with this certification guide, elevating your skills in data processing, storage, and security with the help of practical insights, hands-on exercises, and the latest advancements.

May 2024 18h 16m

Microsoft Power BI Cookbook

Microsoft Power BI Cookbook

Microsoft Power BI is the most sought-after platform for BI professionals' visualization needs. Explore the latest Power BI features, future AI enhancements, and integration with other Power Platform tools via new recipes in this updated edition.

Jul 2024 19h 56m

Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

The book shows you how to clean, wrangle, and view data from multiple perspectives, including dataset and column attributes. You will cover common and not-so-common challenges that are faced while cleaning messy data for complex situations and learn to manipulate data to get it down to a form that can be useful for making the right decisions.

May 2024 16h 12m

Microsoft Azure AI Fundamentals AI-900 Exam Guide

Microsoft Azure AI Fundamentals AI-900 Exam Guide

This AI-900 study guide will help you prepare and practice for the certification exam. You'll delve into AI workloads, ML principles, computer vision, NLP, knowledge mining, and generative AI using Azure cloud services.

May 2024 9h 36m

Using Stable Diffusion with Python

Using Stable Diffusion with Python

This book shows you how to use Python to control Stable Diffusion and generate high-quality images. In addition to covering the basic usage of the diffusers package, the book provides solutions for extending the package for more advanced purposes.

Jun 2024 11h 44m

Getting Started with DuckDB

Getting Started with DuckDB

This hands-on book teaches you to analyze large datasets with blazing speed and ease. You will learn how to use DuckDB to quickly load, query, transform, analyze, and visualize data effectively through a series of practical examples.

Jun 2024 12h 44m

Databricks Certified Associate Developer for Apache Spark Using Python

Databricks Certified Associate Developer for Apache Spark Using Python

This guide gets you ready for certification with expert-backed content, key exam concepts, and topic reviews. Additionally, you'll be able to make the most of Apache Spark 3.0 to modernize workloads and more using specific tools and techniques.