rights reserved. What we’ll cover 1. Kick off a demo (put the cookies in the oven) 2. What’s Deep Learning? What’s a Neural Network? 3. Look at some code 4. Finish the demo (enjoy our cookies) 5. How to do this yourself 6. Where to learn more
rights reserved. Machine Learning A technique to help computers learn how to do things that are easy for humans (but hard to explicitly program). Self-driving Cars Sentiment Analysis Object Detection Facial Recognition
rights reserved. Machine Learning Using neural networks with multiple layers, which allows computers to learn from complex data without needing to explicitly define the features of the data. Neural Networks Deep Learning Computation inspired by how our brains work. Proven to be capable of performing any computation, given enough memory. Computers figuring out how to do things without being explicitly programmed.
rights reserved. Node with a value Neural Network recap linked to other nodes with various connection strengths. Each node value is based on how much of each connecting node’s signal arrives into it, plus some other value to decide what the final value will be. “Neuron” “Weights” “Bias” 2 3 1 5 -4 (1 * 2) + (5 * 3) + -4 = 13 13 Example – Two inputs into a neuron
rights reserved. 0. Randomly initialize the weights and biases (only once at the start). 1. Send each training example through the network, look at the output nodes, and measure the difference between what you wanted to see versus what you actually got. 2. Go backwards through the network, adjust the weights and biases by tiny amounts, trying to nudge the output values closer to what you want to see. 3. Repeat until the network performs well for all of your examples. 4. Run some validation examples through the network to make sure it works for new data, too. Training recap
rights reserved. FRAMEWORKS AND INTERFACES ML for data scientists KERAS Frameworks Inter faces APPLICATION SERVICES ML for everyone PLATFORM SERVICES ML for engineers NVIDIA Tesla V100 GPUs (14x faster than P2) Machine Learning AMIs INFRASTRUCTURE Powering the ML Intel Xeon Skylake (Optimized for ML) AWS GREENGRASS ML L E X P O L L Y R E K O G N I T I O N I M A G E & V I D E O T R A N S C R I B E T R A N S L A T E C O M P R E H E N D F O R E C A S T P E R S O N A L I Z E AMAZON SAGEMAKER AWS DEEPLENS SAGEMAKER GROUND TRUTH & MECHANICAL TURK SPARK & EMR
rights reserved. Amazon SageMaker Build Train Deploy • Managed notebooks for authoring models • Templates for common ML applications • Built-in, high performance algorithms • Broad framework support • One-click training • Automatic model tuning • One-click deployment • Automatic A/B testing • Fully-managed hosting with auto scaling
rights reserved. Detecting the best images to use • Expedia have over 10 million images from 300,000 hotels • Using great images boosts conversion • They fine-tuned a pre-trained Convolutional Neural Network using 100,000 images • Hotel descriptions now automatically feature the best available images https://news.developer.nvidia.com/expedia-ranking-hotel-images- with-deep-learning/
rights reserved. Improving written text with Amazon SageMaker “Amazon SageMaker makes it possible for us to develop our TensorFlow models in a distributed training environment. (…) We can run inference on SageMaker itself, or if we need just the model, we download it from S3 and run inference of our mobile device implementations for iOS and Android customers.”
rights reserved. Great places to get started with Deep Learning 3Blue1Brown’s YouTube series on Neural Networks ~ 60 Minutes https://www.youtube.com/playlist?list=PLZHQObOWTQDNU6R1_67000Dx_ZCJB-3pi Fast.ai’s Practical Deep Learning for Coders ~ 14 Hours http://www.fast.ai/ Neural Networks and Deep Learning, by Michael Neilsen ~ 6 Chapter Book http://neuralnetworksanddeeplearning.com/ Amazon SageMaker - Fully-managed Platform https://aws.amazon.com/sagemaker/ These Demos - Jupyter Notebooks & Web Apps https://github.com/gabehollombe-aws/jupyter-notebooks https://github.com/gabehollombe-aws/webcam-s3-uploader https://github.com/gabehollombe-aws/webcam-sagemaker-inference
awsugmum
recruitengineers
doradora09
yuyatakeyama
ebarakazuhiro
lmi
coconala_engineer
smt7174
taishin
nagix
aeonpeople
foursue
searls
productmarketing
trishagee
frogandcode
jeffersonlam
reverentgeek
bkeepers
jponch
danielanewman
bluesmoon
brettharned
