In this video I show you examples of how to perform transfer learning in various ways, either having trained a model yourself, using keras.applications or the TensorFlow hub. I also show how you can then pick out specific chunks of the pretrained models and remove specific layers, and then how you could freeze those layers, add layers on top and perform fine tuning.

Download TensorFlow Hub (w. pip it's pip install tensorflow-hub):
https://anaconda.org/conda-forge/tensorflow-hub

I learned a lot and was inspired to make these TensorFlow videos by the TensorFlow Specialization on Coursera. Below you'll find both affiliate and non-affiliate links, the pricing for you is the same but a small commission goes back to the channel if you buy it through the affiliate link.
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TensorFlow Playlist:
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A revolution in AI is occurring thanks to progress in deep learning. How far are we towards the goal of achieving human-level AI? What are some of the main challenges ahead?

Yoshua Bengio believes that understanding the basics of AI is within every citizen’s reach. That democratizing these issues is important so that our societies can make the best collective decisions regarding the major changes AI will bring, thus making these changes beneficial and advantageous for all.

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Yoshua Bengio is one of the pioneers of Deep Learning. He is the head of the Montreal Institute for Learning Algorithms (MILA), Professor at the Université de Montréal, member of the NIPS board and co-founder of Element AI. With a PhD from McGill University (1991, Computer Science) and postdocs at MIT and AT&T Bell Labs, he holds the Canada Research Chair in Statistical Learning Algorithms, is a Senior Fellow of the Canadian Institute for Advanced Research and co-directs its program focused on deep learning. He is best known for his contributions to deep learning, recurrent nets, neural language models, neural machine translation and biologically inspired machine learning.

https://mila.umontreal.ca/en/
https://www.elementai.com/

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For more information visit http://www.tedxmontreal.com

This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx

AI Papers Reading and Coding - Transformer: Attention Is All You Need

Hôm nay chúng ta sẽ đọc và lập trình bài báo Transformer: Attention Is All You Need. Đây là video diễn giải phần tiếp theo: Decoder. Một ứng dụng nổi tiếng của Transformer Decoder chính là mô hình sinh GPT, bạn có thể sinh hình quả bơ từ một câu. :D

Đây chính là mô hình xương sống cho những mô hình Deep Learning trong xử lý ngôn ngữ tự nhiên hiện tại.

Code bài báo: https://github.com/bangoc123/transformer

Đây là nội dung trong chuỗi video Papers-Videos-Code: https://protonx.ai/papers-videos-code/