How To Do Transfer Learning For Computer Vision | PyTorch Tutorial

preview_player
Показать описание
Transfer learning is a powerful technique in deep learning for leveraging pre trained networks to generate world class results on new data. PyTorch makes getting started with transfer learning exceptionally easy, and I'll show you how in this tutorial.

Learn how to turn deep reinforcement learning papers into code:

Get instant access to all my courses, including the new Prioritized Experience Replay course, with my subscription service. $29 a month gives you instant access to 42 hours of instructional content plus access to future updates, added monthly.

Or, pickup my Udemy courses here:

Deep Q Learning:

Actor Critic Methods:

Curiosity Driven Deep Reinforcement Learning

Natural Language Processing from First Principles:
Reinforcement Learning Fundamentals

Here are some books / courses I recommend (affiliate links):

Come hang out on Discord here:

Рекомендации по теме
Комментарии
Автор

This content is sponsored by my Udemy courses. Level up your skills by learning to turn papers into code. See the links in the description.

MachineLearningwithPhil
Автор

You are a great teacher, Phil. Thank you!!!

EdwardPie
Автор

Thank for this tutorial. Very clear explanation

danmaina
Автор

Oh my gosh, can u make it too with keras Phil? thanks for everything = D

evertonfonseca
Автор

Great tutorial. How to use pretrained weights in the encoder part of unet model for segmentation

rs
Автор

Your videos are just amazing. 1080p please ?

teetanrobotics
Автор

Love your content, very easy to digest and understand - Would you consider doing a NLP focused video in the future?

SyedZahedi
welcome to shbcf.ru