empowering every person on the planet to achieve more

Dr. Miguel Fierro

Data Scientist at Microsoft

@miguelgfierrohttps://miguelgfierro.com

King’s College London, Industry Talks | Nov 30, 2016 | London

KCL Industry Talk 2016 - Dr. Miguel Fierro @miguelgfierro

source: wikipedia

“Empowering every person and

every organization on the planet

to achieve more” Satya Nadella


Alice in Wonderland


“Oh dear! Oh dear! I shall be too late”


“We’re all mad here.”

“How do you know I’m mad?” said Alice.

“You must be, or you wouldn’t have come here.”


“If you don't know where to go,

any way will take you there,

if you only walk long enough”


“Oh dear! Oh dear! I shall be too late”


Electrical Engineering:Not always that fun


video: https://www.youtube.com/watch?v=CSB8vTjFkGY


“We’re all mad here.”

“How do you know I’m mad?” said Alice.

“You must be, or you wouldn’t have come here.”


link to github: https://github.com/miguelgfierro


code: https://github.com/miguelgfierro/sciblogblog: https://miguelgfierro.com


Mobile first,

cloud first


source: https://github.com/garrett/Tuxsource: https://octoverse.github.com/

Top 1 contributor on Github


source: https://github.com/garrett/Tux


“If you don't know where to go, any way will take you there,

if you only walk long enough”


Not ready yet Ready


Soft robotics

source: http://nms.kcl.ac.uk/core/?page_id=1963

New actuators(Shape Memory Alloy)

source: http://roboticslab.uc3m.es/roboticslab/project/mars-dw

New sensors(Artificial skin)

source: Park et al, 2015 (link to paper)

http://advances.sciencemag.org/content/1/9/e1500661.full


15.4%

7.3%

6.7%

3.6%3.1%

5.1% (human)

error (%)

ImageNet (image recognition competition) top-5 error

AlexNet(2012)

VGG(2014)

Inception(2015)

ResNet(2015)

Inception-ResNet(2016)

AI is ready for

production


LeNet Convolutional Neural NetworkLayers: c=convolution, p=pooling, fc=fully connected


source: https://blogs.technet.microsoft.com/machinelearning/2016/10/31/applying-cloud-deep-learning-at-scale-with-microsoft-r-server-azure-data-lake/


1.

2.

3.

4.

5.

source: https://blogs.technet.microsoft.com/machinelearning/2016/11/15/imagenet-deep-neural-network-training-using-microsoft-r-server-and-azure-gpu-vms/


source: https://blogs.technet.microsoft.com/machinelearning/2016/11/15/imagenet-deep-neural-network-training-using-microsoft-r-server-and-azure-gpu-vms/

Real class

Predicted class


Crepe CNN for Sentiment Analysis

source: Xiang Zhang, Junbo Zhao, Yann LeCun. Character-level Convolutional Networks for Text Classification. NIPS 2015code: https://github.com/ilkarman/Bangalore_Sentiment


Microsoft Research achieves parity with human speech level

source: http://blogs.microsoft.com/next/2016/10/18/historic-achievement-microsoft-researchers-reach-human-parity-conversational-speech-recognition

CNN(VGG, ResNet, LACE)

RNN(Bi-LSTM)

Multi-GPU and multi server(1-bit Stochastic Gradient Descent)


Financial forecasting

Predictive maintenance

Sport analytics

Machine learning research

Rolls-Royce

Real Madrid


DNNs (learn complex patterns)

Intelligent applications

Cloud (flexibility, scalability, efficiency)

Dr. Miguel Fierro

Data Scientist at Microsoft

@miguelgfierrohttps://miguelgfierro.com

King’s College London, Industry Talks | Nov 30, 2016 | London

empowering every person on the planet to achieve more

Leadership & Management