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Hands-On Meta Learning with Python

You're reading from  Hands-On Meta Learning with Python

Product type Book
Published in Dec 2018
Publisher Packt
ISBN-13 9781789534207
Pages 226 pages
Edition 1st Edition
Languages
Author (1):
Sudharsan Ravichandiran Sudharsan Ravichandiran
Profile icon Sudharsan Ravichandiran
Toc

Table of Contents (17) Chapters close

Title Page
Dedication
About Packt
Contributors
Preface
1. Introduction to Meta Learning 2. Face and Audio Recognition Using Siamese Networks 3. Prototypical Networks and Their Variants 4. Relation and Matching Networks Using TensorFlow 5. Memory-Augmented Neural Networks 6. MAML and Its Variants 7. Meta-SGD and Reptile 8. Gradient Agreement as an Optimization Objective 9. Recent Advancements and Next Steps 1. Assessments 2. Other Books You May Enjoy Index

Contributors

About the author

Sudharsan Ravichandiran is a data scientist, researcher, artificial intelligence enthusiast, and YouTuber (search forSudharsan 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.

I would like to thank my amazing parents and my brother, Karthikeyan, for inspiring and motivating me. My big thanks to my best friend, Nikhil Aditya. Huge thanks to Veena Pagare for giving me an amazing opportunity. Special thanks to my dear friend, Sri Hari Charan, who shaped my life. I can't thank enough my best friend, Gautham, for cheering me up through all my tough times, and I am forever grateful to My Soeor, who always has my back.

 

About the reviewers

Gautham Krishna Gudur is a machine learning engineer and researcher working on extracting actionable insights in healthcare (medical wearables) using artificial intelligence. He also does independent research at the intersection of applied machine learning/deep learning, physical activity sensing using sensors and wearable data, computer vision, and ubiquitous computing. Previously, he was a research assistant in the areas of gesture recognition, data science, and IoT at Chennai, India. He actively contributes to the research community by authoring and presenting research publications at renowned conferences around the world. During his undergraduate study, he was also an avid competitive programmer on online platforms such as HackerRank.

Armando Fandangocreates AI-empowered products by leveraging his expertise in deep learning, machine learning, distributed computing, and computational methods, and has fulfilled thought-leadership roles as Chief Data Scientist and Director at start-ups and large enterprises. He has been advising high-tech AI-based start-ups. Armando has authored books titledPython Data Analysis - Second EditionandMastering TensorFlow. He has also published research in international journals and conferences.

 

 

 

 

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