Few-Shot Learning (1/3): Basic Concepts

Показать описание

This lecture introduces the basic concepts of few-shot learning and meta-learning, the definition of "way" and "shot", and two commonly used datasets (Omniglot and Mini-ImageNet).

Lectures on few-shot learning:

Рекомендации по теме

Комментарии

Have literally spent the last couple of days trying to understand few shot learning for a university project and haven't been understanding it at all until this video. Great explanation, thank you so much!

MrSupermonkeyman

Thanks. One of the few videos that explained this concept with near zero jargon.

srh

Wonderful. The best explanation on Few-shot I've seen so far. Thank you!

PD-vtfe

Best lecture about Few-shot learning! Thank you

loading_

Even a toddler can understand this. Thank you.

_chappie_

Best video on this concept! Please keep up the great work! Thank you!

yonghengwang

You save my time to learn this concept. Thank You!

rm

Thank you! the presentation helped me to understand few-show learning.

semacandemir

Man it's difficult to tell between a beaver and an otter

vibhasnaik

Thanks for making it look like a piece of cake. I look forward to many more lectures from you.

_ifly

Extremely clear explanation. Thank you so much.

zoelav

Brilliant, intuitive explanation of few-shot learning! Thank you for uploading.

karanacharya

12:51 Just had to say that your support set image of the two hamsters aren’t hamsters. Those are guinea pigs.

SpenceMan

Thanks for the best explanation ever. I really appreciate your effort.

emanali

Thanks for such a detailed explanation!

anirudhthatipelli

Thank you for this video. It's awesome

x-Factor

Thank you so much for this amazing explanation

souraya

Awesome!!! A Great presentation, Thank you!

nannuakand

your lectures are very easy to understand. Keep it up👍

mmazher

Hello, I found this video helpful. Could you maybe also upload the other parts? Thank you.

liminm

Few-Shot Learning (1/3): Basic Concepts

Few-Shot Learning (1/3): Basic Concepts

Few Shot Learning - EXPLAINED!

Zero-shot, One-shot and Few-shot Prompting Explained | Prompt Engineering 101

FEW-SHOT LEARNING | Basic concepts | Introduction to Natural Language Processing (NLP) | 02

Few-Shot Learning (FSL) || Meta Learning || Few-Shot Learning Basic Concepts || One Shot Learning

Few-Shot Learning - Part1: Introduction

Few Shot Learner | Computer Vision | Refrigerated Product Classifier

Few-shot learning with SetFit

Mengye Ren - Towards Continual and Compositional Few-shot Learning

Few-Shot Learning & Meta Learning

Corporate-Talk Chatbot: Few-Shot Learning, Large Language Models Explained Prompt Engineering Course

Few-Shot Learning (FSL) Approaches || How few shot learning work || Meta Learning Approaches

Few Shot Learning with Code - Meta Learning - Prototypical Networks

Few-Shot Learning of Part-Specific Probability Space for 3D Shape Segmentation

Few-shot learning in production

Few-shot and Zero-shot Learning - Part 01

One Shot Learning - A Must Know Deep Learning Concept.

Generalized and Incremental Few-Shot Learning by Explicit Learning & Calibration without Forgett...

Chelsea Finn -- Few Shot Learning in the Real World: Meta-Learning for Giving Feedback to Students

SQL Translation Bot: Few-Shot Learning, Large Language Models Explained — Prompt Engineering Course...

Few-Shot Incremental Learning (1-minute talk at CVPRW 2020)

Beginner Aim Technique Pool Shot #shorts #pool #aim #beginners #tip #strategy #cutshot

DPGN: Distribution Propagation Graph Network for Few-Shot Learning

FIX Your Jump Shot Instantly With This Tip! 🏀 #shorts