What we're about

Welcome to the IBM Code London Meetup!

Latest News: our new office is now based in wework Moorgate :)

We're running a series of hands-on workshops (BYOD*) on a variety of technologies:

- Cloud Native Development and Containers
- Internet of Things
- Artificial Intelligence and Machine Learning
- Data Science
- Blockchain

Each of these tracks will be split in to several workshops diving deeper in to the subject each time.

What you can expect during our Meetups: Hands-on, talks, networking, food and drinks!

We hope to see you at our events!
IBM Developer Advocacy team

* Bring Your Own Device

Missed a session? All content is made available on: http://ibm.biz/content-code-ldn

Code of Conduct : https://github.com/IBMCodeLondon/infos/blob/master/code-of-conduct.md (https://github.com/arlemi/IBMCode_London/blob/master/code-of-conduct.md)

Upcoming events (4)

Deep Learning 101 – The rise of the GPU

CodeNode - Skills Matter

This series gives you a quick overview of several deep learning frameworks. With each framework, you’ll learn about the framework’s benefits, supported platforms, installation considerations, and supported back ends. Deep learning isn’t a single approach but rather a class of algorithms and topologies that you can apply to a broad spectrum of problems. While deep learning is certainly not new, it is experiencing explosive growth because of the intersection of deeply layered neural networks and the use of GPUs to accelerate their execution. Big data has also fed this growth. Because deep learning relies on supervised learning algorithms, the more data, the better to build these deep learning structures. Agenda: 18.30 - 19.00 : Registration, Food, Drinks and Networking 19.00 - 21.00 : Introduction, followed by a walkthrough of the Use Case Why GPUs Matter For Deep Learning ~ 15 mins What even is "Deep Learning"? Seriously, behind the scenes, how does this stuff work? We'll see a really quick worked example for recognising hand written digits, discussing the theory, and the infrastructure limitations that make GPUs THE platform for Deep Learning. Working with BIG data - Going beyond a GPU ~ 15 mins As we continually search for bigger, more complicated, problems the demands we place on the GPU continue to grow rapidly. So where next - how can we continue to build models and algorithms that scale as our data does or enable us to tackle even more intricate problems? In this session we'll talk about the Open Source Large Model Support. IBM's solution to the problem that enables TensorFlow, Caffe and PyTorch developers to overcome the GPU memory limitation and keep growing their deep learning workloads. Style Transfer - Replicating Art with AI (LAB) ~ 60 mins In our hands on lab we'll discuss how Style Transfer can be used to take the "style" or visual effect from one image and apply it to another, mimicking the style of an artist. We'll explore the theory behind the process, before getting hands on and running our own Jupyter notebook in Watson Studio to perform Style Transfer on our own images using the Watson Machine Learning service. Speaker: Chris Parsons - Machine Learning Developer Advocate

Deep Learning 101 – The rise of the GPU

CodeNode - Skills Matter

This series gives you a quick overview of several deep learning frameworks. With each framework, you’ll learn about the framework’s benefits, supported platforms, installation considerations, and supported back ends. Deep learning isn’t a single approach but rather a class of algorithms and topologies that you can apply to a broad spectrum of problems. While deep learning is certainly not new, it is experiencing explosive growth because of the intersection of deeply layered neural networks and the use of GPUs to accelerate their execution. Big data has also fed this growth. Because deep learning relies on supervised learning algorithms, the more data, the better to build these deep learning structures. Agenda: 18.30 - 19.00 : Registration, Food, Drinks and Networking 19.00 - 21.00 : Introduction, followed by a walkthrough of the Use Case Why GPUs Matter For Deep Learning ~ 15 mins What even is "Deep Learning"? Seriously, behind the scenes, how does this stuff work? We'll see a really quick worked example for recognising hand written digits, discussing the theory, and the infrastructure limitations that make GPUs THE platform for Deep Learning. Working with BIG data - Going beyond a GPU ~ 15 mins As we continually search for bigger, more complicated, problems the demands we place on the GPU continue to grow rapidly. So where next - how can we continue to build models and algorithms that scale as our data does or enable us to tackle even more intricate problems? In this session we'll talk about the Open Source Large Model Support. IBM's solution to the problem that enables TensorFlow, Caffe and PyTorch developers to overcome the GPU memory limitation and keep growing their deep learning workloads. Style Transfer - Replicating Art with AI (LAB) ~ 60 mins In our hands on lab we'll discuss how Style Transfer can be used to take the "style" or visual effect from one image and apply it to another, mimicking the style of an artist. We'll explore the theory behind the process, before getting hands on and running our own Jupyter notebook in Watson Studio to perform Style Transfer on our own images using the Watson Machine Learning service. Speaker: Chris Parsons - Machine Learning Developer Advocate

Chatbots 201 - Enhance your chatbot!

CodeNode - Skills Matter

This workshop is directed to people who are interested in chatbots and: - have attended one of our previous chatbot workshop - have a previous experience with chatbot services (DialogFlow, Watson Assistant) and understand the concept of Intents and Entities If you're interested in joining but don't don't know much about chatbots yet, don't worry: you can run through the Introduction to Watson Assistant workshop before the event here: https://github.com/IBMDeveloperUK/chatbot-workshop/blob/master/training.md During the hands-on we'll be looking at how it is possible to enhance a chatbot with advanced features (slots, system entities, context variable and Spring Expression Language) as well as how to integrate Natural Language Understanding to better understand user sentiment. We'll provide you with an existing chatbot to save time and so you can get to the real stuff straight away! This is a hands-on session so please bring a laptop along. Agenda: 18.30 - 19.00: Registration, Food, Drinks and Networking 19.00 - 19.15: Quick reminder on chatbots and Natural Language Understanding 19.15 - 21.00: Hands on workshop Speaker: Arlemi - Developer Advocate (@arlemi)

Kubernetes 101

CodeNode - Skills Matter

--------------- PLEASE NOTE: This a rerun of the Kubernetes 101 workshop in 2018. The content will be identical. --------------- Kubernetes is one of the most popular technologies in cloud computing at the moment but it can be really confusing at times. Running containers in production is a tricky challenge but Kubernetes makes it a lot easier. Come along to this free workshop, learn about container orchestration and get hands-on experience in managing a container cluster with Kubernetes. This is a workshop is aimed at people who have no experience with Kubernetes. A basic understanding of containers will be helpful but is not required. Please bring your laptop for the hands-on lab. Agenda: 18.30 - 19.00: Registration, Food, Drinks and Networking 19.00 - 19.30: Introduction 19.30 - 21.00: Hands on workshop (Kubernetes) Workshop material and slides will be made available on Github. Speakers: Ed Shee - Developer Advocate Mofe Salami - Developer Advocate Wednesday 13th February,[masked]:30 PM to 9:00 PM CodeNode - Skills Matter 10 South Place, London, EC2M 7EB, GB · London

Past events (41)

Kubernetes 101

CodeNode - Skills Matter

Photos (106)