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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

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Product type Paperback
Published in Apr 2020
Publisher Packt
ISBN-13 9781838825461
Length 156 pages
Edition 1st Edition
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Authors (2):
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Ankush Garg Ankush Garg
Author Profile Icon Ankush Garg
Ankush Garg
Shruti Jadon Shruti Jadon
Author Profile Icon Shruti Jadon
Shruti Jadon
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Toc

Table of Contents (11) Chapters Close

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

Setting up your environment

In this section, we will set up a virtual environment for our coding exercise and questions using the following steps:

  1. Clone the repository by going into the directory of your choice and running the following command in the Git Bash command line:
git clone https://github.com/Packt-Publishing/Hands-on-One-Shot-Learning.git
  1. Go to the Chapter01 directory of the cloned repository:
cd Hands-on-One-Shot-Learning/Chapter01
  1. Then, open a Terminal and use the following command to install Anaconda for Python, version 3.6 (https://docs.anaconda.com/anaconda/install/), and create a virtual environment:
conda create --name environment_name python=3.6
In steps 3 and 4, you can replace environment_name with an easy name to remember, such as one_shot, or a name of your choice.
  1. Activate the environment using the following command:
source activate environment_name...
You have been reading a chapter from
Hands-On One-shot Learning with Python
Published in: Apr 2020
Publisher: Packt
ISBN-13: 9781838825461
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