MACHINE LEARNING

A Technical For Technical People

TECH SESSIONS
Thursday, December 7th
18:00 – 21:00

 

In Partnership With
SherlockML by ASI Data Science    

View Content

MACHINE LEARNING

A Technical For Technical People

TECH SESSIONS
Thursday, December 7th
18:00 – 21:00

 

In Partnership With
SherlockML by ASI Data Science    

View Content

A technical event for technical people.

FOUR INDUSTRY CASE STUDIES
ONE ML START-UP PITCH
KEY NETWORKING
LOTS OF CONTENT

This is a learning event. No high-level vagueness, just powerful insights for you.

Themes:
{Machine Learning} {Automation} {Articial Intelligence} {Predictive Analytics}

A technical event for technical people.

FOUR INDUSTRY CASE STUDIES
ONE ML START-UP PITCH
KEY NETWORKING
LOTS OF CONTENT

This is a learning event. No high-level vagueness, just powerful insights for you.

Themes:
{Machine Learning} {Automation} {Articial Intelligence} {Predictive Analytics}

Event Schedule

18:00
Event Check-In & Networking

---------

18:30 - 18:50
Natural Language Processing
in Media: Challenges and Opportunities

Xiaolan Sha - Data Scientist @ Sky
Xiaolan Sha, Lead Data Scientist, Sky

Key Takeaways

Talk:
Natural language processing facilitates media planners in textual context extraction.
It learns human language elements, great for pinning key concepts, but still far from delivering us a Game of Thrones episode 🙂

Structure of Sky's data function:centralised
Favourite ML use case: bots trained to play Mario Kart using Generative Adversarial Networks


---------

18:50 - 19:00
Machine Learning for Customer Support Augmentation

Nigel Ng, Data Science @ Monzo
Nigel Ng, Data Scientist, Monzo

Key Takeaways

Talk:
- Going beyond classification for a more general purpose/flexible model
- How we handle short term discrepancies (i.e. if there's an outage or other anomalies in queries)
- Our experience switching from Tensorflow to Pytorch
- Some findings on Pytorch vs Keras


---------

18:50 - 19:00
Modern Techniques for Dimensional Reduction

Ilya Feige, Head of Research @ ASI Data Science
Ilya Feige, Head of ML Research, SherlockML

Key Takeaways

Talk:
- What is dimensional reduction and how/why you should use it
- How t-SNE and PCA work as two distinct ML methods
- Witness some amazing results using t-SNE!


---------

19:10 - 19:30
The Impact of
Automation at Scale

Mike Todd, Chief Data Scientist @ Deliveroo
Mike Todd, Chief Scientist, Deliveroo

Key Takeaways

Talk:
- Deliveroo presents a rare glimpse at the impact of automation, because it reached international scale before automating much of its core delivery processes.
- Automating dispatch and delivery rider booking machinery continues to have massive, experimentally measurable impact.
- This journey highlights the power of incrementalism, because replacing elaborate, regionally specific, manual processes with simple, central, automatic processes is incredibly successful.

Structure of Deliveroo's data function: embedded
GDPR advice: Hire a data security expert
#1 skills for 2018: Reading computer age statistical inference


---------

19:30 - 19:50
Machine Learning at Zopa

Vlasios Vasileiou, Head of Data Science @ Zopa
Vlasios Vasilieou, Head of Machine Learning, Zopa

Key Takeaways

Talk:
How we do training and deployment of ML models

Structure of Sky’s data function: democratised
Most important skill for 2018: Data governance strategies


---------

20:10 - 21:30
Networking & Drinks

This is your chance to meet the speakers and your fellow machine learning enthusiasts, making connections that go well beyond this evening!

Event Schedule

Check-In & Networking
18:00

Xiaolan Sha, Data Scientist @ Sky

Natural Language Processing in Media: Challenges and Opportunities
Xiaolan Sha, Lead Data Scientist, Sky
18:30 - 18:50
LinkedIn

Key Takeaways

Talk: Natural language processing facilitates media planners in textual context extraction.
It learns human language elements, great for pinning key concepts, but still far from delivering us a Game of Thrones episode 🙂

Structure of Sky's data function: centralised
Favourite ML use case: bots trained to play Mario Kart using Generative Adversarial Networks

Nigel Ng, Data Science @ Monzo

The Inner Workings of Monzo's Help Search Algorithm
Nigel Ng, Data Scientist, Monzo
18:50 - 19:00
GitHub

Key Takeaways

Talk:
- Going beyond classification for a more general purpose/flexible model
- How we handle short term discrepancies (i.e. if there's an outage or other anomalies in queries)
- Our experience switching from Tensorflow to Pytorch
- Some findings on Pytorch vs Keras

Ilya Feige, Head of Research @ ASI Data Science

Modern Techniques for Dimensional Reduction
Ilya Feige, Head of ML Research, SherlockML
19:00 - 19:10
LinkedIn

Key Takeaways

Talk:
- What is dimensional reduction and how/why you should use it
- How t-SNE and PCA work as two distinct ML methods
- Witness some amazing results using t-SNE!

Mike Todd, Chief Data Scientist @ Deliveroo

The Impact of Automation at Scale
Mike Todd, Chief Scientist, Deliveroo
19:10 - 19:30
LinkedIn

Key Takeaways

Talk:
- Deliveroo presents a rare glimpse at the impact of automation, because it reached international scale before automating much of its core delivery processes.
- Automating dispatch and delivery rider booking machinery continues to have massive, experimentally measurable impact.
- This journey highlights the power of incrementalism, because replacing elaborate, regionally specific, manual processes with simple, central, automatic processes is incredibly successful.

Structure of Deliveroo's data function: embedded
GDPR advice: Hire a data security expert
#1 skills for 2018: Reading computer age statistical inference

Vlasios Vasileiou, Head of Data Science @ Zopa

Machine Learning at Zopa
Vlasios Vasileiou, Head of Data Science, Zopa
19:30 - 19:50
LinkedIn

Key Takeaways

Talk: How we do training and deployment of ML models

Structure of Sky’s data function: democratised
Most important skill for 2018: Data governance strategies

Networking & Drinks
20:10 - 21:30

This is your chance to meet the speakers and your fellow machine learning enthusiasts, making connections that go well beyond this evening!

Featured Content

https://speakerdeck.com/techsessions/the-inner-workings-of-monzos-help-search-algorithm
https://speakerdeck.com/techsessions/modern-techniques-for-dimensional-reduction
https://speakerdeck.com/techsessions/natural-language-processing-in-media-challenges-and-opportunities
https://speakerdeck.com/techsessions/machine-learning-at-zopa
https://speakerdeck.com/techsessions/the-impact-of-automation-at-scale

Featured Content

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