LEARN FROM THE BEST TRAINERS IN THE CLOUD

  • 2
    Days
  • 2
    Trainers
  • 100
    Attendees
ML WORKSHOPS FOR ENGINEERS

The workshops from the list below are the complimentary part of full tickets. The full workshop program will be published soon! The registration will be available as soon as the schedule will be finalized.

The recordings of most workshops will be shared with full ticket holders after the conference.

Workshops will be run remotely via Zoom.

Jason Mayes

Hands on with TensorFlow.js

Attended the TensorFlow.js 101 talk and feeling inspired? Come check out our workshop which will walk you through 3 common journeys when using TensorFlow.js. We will start with demonstrating how to use one of our pre-made models - super easy to use JS classes to get you working with ML fast. We will then look into how to retrain one of these models in minutes using in browser transfer learning via Teachable Machine and how that can be then used on your own custom website, and finally end with a hello world of writing your own model code from scratch to make a simple linear regression to predict fictional house prices based on their square footage.

Prerequisites

Workshop requires some working knowledge of using HTML / CSS / JS to get the most out of it. No Machine Learning background is assumed.

Attending TensorFlow.js 101 talk is highly recommended to get the most out of the session.

Workshop level

Great for beginners or researchers looking to get the reach and scale of web technologies so more people can use their models. No ML knowledge is assumed.

Workshop schedule & location

The schedule will be announced later. The workshop will be recorded.

Mikhail Burtsev

AI Assistant with DeepPavlov

Simple chatbots can be built with a number of simple rules, but their UX will be very narrow and limited. Building complex AI assistants, in contrast, requires a lot of effort. To make your users happy, you have to master many things at once: rules, intents, finite state machines, chit-chat tech, dialog flow management, and many other things. It's a job for an entire team. Fortunately, you don't have to hire it. Instead, you can rely upon your trusty software from DeepPavlov.ai. With it, you can offload the complexity of managing the entire infrastructure to DeepPavlov Agent – an open-source Conversational AI orchestrator. Next, you can pick state-of-the-art NLP components from DeepPavlov Library to decode human emotions and understand their intents. Finally, you can pick some of the available skills from DeepPavlov Dream to avoid reinventing the wheel like chit-chat.

In this workshop, you'll be guided through the entire process, from an overview of the platform to building a sample AI assistant that you'll be able to re-use later in your own work.

By the end of this workshop you'll be able to use the provided components from the DeepPavlov family of projects to build simple AI assistant:

  • work with existing NLP components from DeepPavlov Library like sentiment and emotion classifiers
  • build simple goal-oriented skill with DeepPavlov Go-Bot
  • combine them together with the DeepPavlov Agent into a simple AI assistant
  • augment your simple AI assistant with some of the DeepPavlov Dream pre-built skills
Workshop level

Intermediate or Advanced.

Workshop schedule & location

The schedule will be announced later. The workshop will be recorded.

Jason Mayes
Google, USA

Jason is a Senior Developer Advocate for TensorFlow.js at Google.

Jason combines his knowledge of the technical and creative worlds to solve complex, strategic / technical challenges for Google's largest customers and internal teams. Developing innovative world firsts utilizing the latest technologies and hardware is a key component of his role to rapidly prototype new ideas and consult on project solutions globally.

With a background in Computer Science at the University of Bristol, England, where he specialized in reality mining and invisible computing, Jason has been a "hybrid engineer" for over 15 years. Combining his passion for several areas including both front and back end web programming, but also design and user experience, he has worked in many sizes of companies from startups (including founding his own) to Google.

Mikhail Burtsev
DeepPavlov.ai, Russia

Mikhail Burtsev is a head of Neural Networks and Deep Learning Laboratory at Moscow Institute of Physics and Technology. He is also a founder and leader of open-source conversational AI framework DeepPavlov. Mikhail had proposed and co-organize a series of academic Conversational AI Challenges (including NIPS 2017, NeurIPS 2018, EMNLP 2020).

His research interests are in the fields of Natural Language Processing, Machine Learning, Artificial Intelligence and Complex Systems. Mikhail Burtsev has published more than 20 technical papers including – Nature, Artificial Life, Lecture Notes in Computer Science series, and other peer-reviewed venues.