fast.ai - learning deep learning

Learning Deep Learningfast.ai course

Teemu Kurppa - www.teemukurppa.net Head of Cloud , ŌURA - ouraring.com Twitter - @teemu

teemu@ouraring.com

www.ouraring.com

the world's first wellness ring

Head of Cloud

I work at

Hype is strongwith this one

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AI Winters60s70s80s90s

This time it’s different?

Jeremy HowardEntrepreneur & Data Scientist

FastMailfamous email service

Kaggledata science competitions

Enlitic using deep learning for medical imaging

fast.aimaking deep learning accessible to all

fast.ai course - the method

Learn to apply first - learn theory after

7 lessons: - video lectures, 1-2h/each - assignments & reading, +10h/lesson - Kaggle competitions

fast.ai course - Part 1 contentImage Recognition Collaborative Filtering Natural Language Processing

Underfitting Overfitting

Semi-supervised learning CNNs, RNNs, Embeddings

Transfer Learning

Transfer Learning

Finetune this

Reuse this

from vgg16 import Vgg16vgg = Vgg16()

batch_size=64

batches = vgg.get_batches(path+'train', batch_size=batch_size) val_batches = vgg.get_batches(path+’valid’, batch_size=batch_size*2)

vgg.finetune(batches) vgg.fit(batches, val_batches, nb_epoch=1)

vgg.test(path+’test’)

Lesson 1: Code

Gives 97% accuracy (State of the Art 3 years ago 80%)

State of the Art Techniques

2011 Xavier Initialisation2013 VGG2014 Pseudo-labeling2014 Dropout 2015 Batch Normalisation2015 ResNet2016 VGG with Batch Norm (by Jeremy)

AI Garage Helsinki

regular monthly meet-up for programmers learning by doing

Interested?

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Teemu Kurppa - www.teemukurppa.net Head of Cloud , ŌURA - ouraring.com Twitter - @teemu