Hands-On Meta Learning with Python
This is the code repository for Hands-On Meta Learning with Python, published by Packt.
Meta learning using one-shot learning, MAML, Reptile, and Meta-SGD with TensorFlow
What is this book about?
Meta learning is an exciting research trend in machine learning, which enables a model to understand the learning process. Unlike other ML paradigms, with meta learning you can learn from small datasets faster.
This book covers the following exciting features:
- Understand the basics of meta learning methods, algorithms, and types
- Build voice and face recognition models using a siamese network
- Learn the prototypical network along with its variants
- Build relation networks and matching networks from scratch
- Implement MAML and Reptile algorithms from scratch in Python
If you feel this book is for you, get your copy today!
Instructions and Navigations
All of the code is organized into folders. For example, Chapter02.
The code will look like the following:
import re
import numpy as np
from PIL import Image
Following is what you need for this book:
Hands-On Meta Learning with Python is for machine learning enthusiasts, AI researchers, and data scientists who want to explore meta learning as an advanced approach for training machine learning models. Working knowledge of machine learning concepts and Python programming is necessary.
With the following software and hardware list you can run all code files present in the book (Chapter 2-8).
Software and Hardware List
| Chapter | Software required | OS required |
|---|---|---|
| 2-8 | Python | Windows, Mac OS X, and Linux (Any) |
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Get to Know the Author
Sudharsan Ravichandiran is a data scientist, researcher, artificial intelligence enthusiast, and YouTuber (search for Sudharsan reinforcement learning). He completed his bachelor's in information technology at Anna University. His area of research focuses on practical implementations of deep learning and reinforcement learning, which includes natural language processing and computer vision. He is an open source contributor and loves answering questions on Stack Overflow. He also authored a best-seller, Hands-On Reinforcement Learning with Python, published by Packt Publishing.
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