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Meet up

Machine Learning: The Julian Approach

Monday, 16th October at CodeNode, London

This meetup is run by London Julia Users Group. Starts at 6:30 PM.

Machine learning is one of the fastest growing Julia Community group. It featured in a workshop session at JuliaCon 2017, part of which was presented by one of this meetup's speakers.

Machine Learning: The Julian Approach

Machine learning is one of the fastest growing Julia Community group. It featured in a workshop session at JuliaCon 2017, part of which was presented by one of this meetup's speakers.

Some ML packages have fallen by the wayside and others are now in the ascendency and in this talk Mike and Avik will discuss what the favoured options are for tackling machine and deep learning problems in Julia and in addition will discuss some of the exciting developments which will be available soon.

Mike Innes and Avik Sengupta are no strangers to the London User Group, each having authored a number of seminal Julia packages. Both now are full time employees of Julia Computing in the UK and are well placed to provide key information as to the way ahead to Julia v1.0

Mike Innes

Mike is a recent physics graduate who managed to combine his undergraduate studies with a number of seminal packages such as Markdown, Lazy, Atom and Blink. He started the Juno project while studying for his degree and now works on it full time for MIT and Julia Computing.

Machine Learning: The Julian Approach

Machine learning is one of the fastest growing Julia Community group. It featured in a workshop session at JuliaCon 2017, part of which was presented by one of this meetup's speakers.

Some ML packages have fallen by the wayside and others are now in the ascendency and in this talk Mike and Avik will discuss what the favoured options are for tackling machine and deep learning problems in Julia and in addition will discuss some of the exciting developments which will be available soon.

Mike Innes and Avik Sengupta are no strangers to the London User Group, each having authored a number of seminal Julia packages. Both now are full time employees of Julia Computing in the UK and are well placed to provide key information as to the way ahead to Julia v1.0

Avik Sengupta

Avik Sengupta has build risk and trading systems in Java for investment banks for over a decade. Four years ago he discovered Julia, and hasn’t looked back since. He is a major Julia contributor and the maintainer of various Julia packages.

Thanks to our sponsors

Attending Members

Overview

Machine learning is one of the fastest growing Julia Community group. It featured in a workshop session at JuliaCon 2017, part of which was presented by one of this meetup's speakers.

Machine Learning: The Julian Approach

Machine learning is one of the fastest growing Julia Community group. It featured in a workshop session at JuliaCon 2017, part of which was presented by one of this meetup's speakers.

Some ML packages have fallen by the wayside and others are now in the ascendency and in this talk Mike and Avik will discuss what the favoured options are for tackling machine and deep learning problems in Julia and in addition will discuss some of the exciting developments which will be available soon.

Mike Innes and Avik Sengupta are no strangers to the London User Group, each having authored a number of seminal Julia packages. Both now are full time employees of Julia Computing in the UK and are well placed to provide key information as to the way ahead to Julia v1.0

Mike Innes

Mike is a recent physics graduate who managed to combine his undergraduate studies with a number of seminal packages such as Markdown, Lazy, Atom and Blink. He started the Juno project while studying for his degree and now works on it full time for MIT and Julia Computing.

Machine Learning: The Julian Approach

Machine learning is one of the fastest growing Julia Community group. It featured in a workshop session at JuliaCon 2017, part of which was presented by one of this meetup's speakers.

Some ML packages have fallen by the wayside and others are now in the ascendency and in this talk Mike and Avik will discuss what the favoured options are for tackling machine and deep learning problems in Julia and in addition will discuss some of the exciting developments which will be available soon.

Mike Innes and Avik Sengupta are no strangers to the London User Group, each having authored a number of seminal Julia packages. Both now are full time employees of Julia Computing in the UK and are well placed to provide key information as to the way ahead to Julia v1.0

Avik Sengupta

Avik Sengupta has build risk and trading systems in Java for investment banks for over a decade. Four years ago he discovered Julia, and hasn’t looked back since. He is a major Julia contributor and the maintainer of various Julia packages.

Thanks to our sponsors

Who's coming?

Attending Members