Skip to content

Meeting #26: Machine Learning & Serverless

Photo of Jon Green
Hosted By
Jon G. and Stephen W.
Meeting #26: Machine Learning & Serverless

Details

Details

In this meeting we have two great presentations (with Demo's) for you by Evangelist and regular visitor Danilo Poccia! Firstly, Danilo will be showing us how he has developed a serverless chat bot that performs sentiment analysis and automated translation. The second presentation will be on how you can use Machine Learning to conduct Serverless Analytics in order to extract insights and actionable information in a cost-effective manner.

Some great talks!

We are hosted, as ever, by our dear friends from Metail.

We look forward to welcoming you!

18:30: Arrival

19:00: Announcements - Jon Green (Adeptium)

19:10: PRESENTATION/DEMO: “Building a serverless positive chat and why products and teams are important" - Danilo Poccia (AWS)

Can we use technology to improve ourselves? Communication is such an important part of our lives, and we should always strive to improve - but it is not easy. I'll show how I came to build a serverless "positive chat" using sentiment analysis and automatic translation to provide a more inclusive environment. And as I was building, a few ideas popped into my mind. When you build something new, what is the meaning of a 1.0 release? And when we work together, what is the role of a team?

20:10: Break

20:20 : PRESENTATION/DEMO: "Using Machine Learning for Serverless Analytics" - Danilo Poccia (AWS)

Extracting insights and actionable information from data requires a broad array of technology that can work with data in an efficient, scalable, and cost-effective way. AWS offers a comprehensive set of services to handle every step of the analytics process chain, without having to think about servers and the underlying infrastructure. In this session, we’ll implement step-by-step a serverless analytics platform that can process static content (such as files) or real-time data (such as video, audio, application logs, website clickstreams, and IoT telemetry), enrich data using API-driven machine learning services, query data instantly, and build visualizations to perform ad-hoc analysis.

21:20 Social, Pizza, Networking, Close.

As usual Metail will be hosting us for this evening and will be providing refreshments.

How to get here:

Metail's based at Janus House, which is next door but one and above of Sainsburys local store

By car:

Park at Queen Anne's Car Park on Gonville Place, walk across Parker's Piece opposite, towards the University Arms (big hotel), and then along St Andrew's St. in the same direction.

Or park at any Park and Ride car park, take the bus into town, and get off at Drummer Street. Walk down Emmanuel St. to St Andrew's St., turn left, and it's about 200yds on the left.

By train:

To Cambridge Station, then walk down Station Road to Hill's Road junction. Turn right, and it's about a mile's walk. Or catch the Citi 1, Citi 3 or Citi 8 (or 1A) bus from the Station, towards town - the bus stops are to the left, as you exit the station. Get off when you see a Sainsburys on the right!

By bus:

Too many bus routes serve the area to cover here: quite a lot of them stop just outside. Check the Cambridge Buses ( https://www.cambridgeshire.gov.uk/info/20017/buses ) website for details.

By bike:

There are a few bike loop sets nearby. The closest is directly opposite the main entrance outside the council building, also just round the corner near the Mai Thai restuarant and a tiny bit further on the otherside of the University Arms by Pizza Hut. Those are all exposed. There's an underground bike park in the Lion Yard/Grand Arcade. The bike entrance is just under Carluccio's.

Photo of Cambridge AWS User Group group
Cambridge AWS User Group
See more events