Machine learning practitioners quickly reach the limit of their own computers, especially if they are dealing with big data sets. The solution for this problem is to train machine learning models using cloud services.

I will talk about how to train and deploy neural network models on Google Cloud. I will give an overview of a Trustpilot fraud detection service that is deployed on ML Engine. Furthermore, I will give a tutorial on training neural networks with Keras on ML Engine. This tutorial will help the beginner-level ML Engine user navigate this new landscape.

• Overview of a TrustPilot ML engine service in production - a spam review detector
• A tutorial on training neural networks on GCP

Experience the journey, as it has just begun, of an AI enthusiast with the story featuring a college graduate, seeking something new and exciting to work on, landing up into DL and AI. The word AI has been around us since the 80s but we were just not smart enough to understand it and our computers were not fast enough to perform the computation associated with it at a large scale. A part of the talk feature what is Deep Learning & AI and what I have learned from the influential people in the industry.

Zeeshan is a student at DTU where he studies Machine Learning.

Knative provides a set of middleware components that are essential to build modern, source-centric, and container-based applications that can run anywhere: on premises, in the cloud, or even in a third-party data center. Knative components are built on Kubernetes and codify the best practices shared by successful real-world Kubernetes-based frameworks. It enables developers to focus just on writing interesting code, without worrying about the “boring but difficult” parts of building, deploying, and managing an application.

You can use Dialogflow and Google Cloud Platform for many reasons, we can create interactions to be used within your own communities, may it be a conversational app for families, companies, sports; to help workflows for both customers and businesses. Sometimes it can be a bad thing to talk to an automated conversation if it is not well-designed.

These pieces of technology can also help you escalate the conversation to a real human, as it can help you detect when human intervention is needed by using the ability of sentiment analysis, leveraging both sides of AI and Machine Learning in one computer-human interaction platform.

Everyone at all levels is welcome to attend this talk!

Amanda Cavallaro is a software developer, passionate about Cloud technologies, Human Computer Interactions and conversational apps. She works at http://resolver.co.uk and is a Women Techmakers Lead and Community Organiser at GDG Cloud London. You can speak to her in Portuguese, English, Italian and a little of Japanese. More info on her personal website: http://amanda.ml

In this talk Ahmed will show how you can set up Kubernetes and how he configured it and sat it up at the company he worked at. He will talk about his experience and what tips and tricks he learned while still being efficient.