What is NDR?

NDR is an artificial intelligence conference. Well, technically, it’s an artificial intelligence, and machine learning, and deep learning, and data science conference. We don’t discriminate :).

NDR-113 is also the main character in Isaac Asimov’s beautiful sci-fi novel, The Positronic Man. The book tells of a robot that begins to display human characteristics, such as creativity, emotion, and self-awareness. We felt that naming our conference after him was an appropriate homage to the story.

NDR is something we think you’re going to love.


Chopin Hall, Palas Ensemble
Iasi, Romania

June 7th, 2018


The good people at Strongbytes and Codecamp, naturally.

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Bringing Great Minds Together

Your chance to meet international experts and learn from their experience

We aim to bring together practitioners of data science, machine learning and deep learning. Filled with selected technical talks, our conference is designed to educate and inspire the audience, with experienced speakers discussing their own experiences, showcasing best practices, and business use cases.

An Energising Experience

1 day, 1 track, 11 sessions

At the end of the day you’ll come out excited and exhausted, wanting more. You will get a better understanding of how to build intelligent applications, and see how companies are using intelligent techniques in production. You will find out about new tools and techniques, how you can improve your workflow, or how you can start your data science career.

See you there!

NDR is coming up in
  • Regular

    Full-price tickets, available starting May 8th
  • Access to the full conference, coffee and snacks
  • 79
  • Early-Bird

    Discounted pricing, available only until May 7th
  • Access to the full conference, coffee and snacks
  • 49

Our Speakers

Conference Schedule

  • June 7th

  • 09:15 - 09:45
    How can organizations optimize their sales channels and product targeting? Can you automate first line of support and improve customer satisfaction? How do I protect my online payment channel from frauds? These and more questions are addressed in this session about building smarter business applications that leverage the capability of Artificial Intelligence technologies. Come and see in practice Azure Machine Learning, Microsoft Cognitive Services and the Bot Framework for building intelligent applications that analyze data and predict better outcomes for businesses.

  • 09:45 - 10:15
    Online advertising is an essential component of any business strategy. Every year, the investment on online advertising grows for mobile and web. To meet this growing demand, many online ad publishers build their own ad serving platforms to manage and deliver ad inventory. As a consequence, the need of click prediction systems are crucial for the success of such systems. In this talk, I will introduce the importance of click prediction in ad servers and some of the challenges found when building click prediction models. I then explore some of the most simple algorithms used to tackle click prediction as well as some of the parameters that mostly impact performance.

  • 10:30 - 11:00
    An insight into the creation of a graph based, quantum inspired neural network that outperforms the Big Players (Google, IBM, Microsoft and Alexa) in Natural Language Processing.

  • 11:00 - 11:30
    Common approaches to measuring how well a new model performs can be highly misleading, and simply picking the one with the highest precision/recall can ruin your product. I'll explain how and look at some simple approaches you can use in your workflow to combat this which we use in Dimensions, as well as some larger organisational changes that may be required.

  • 11:45 - 12:15
    Recommender systems are used to increasingly shape your behavior online, recommending you everything from the clothes you wear to the music you listen to, to the people you become friends with. In this talk we will take a look at the major types of recommender systems, how they work including advantages and disadvantages, and how they can be used effectively.

  • 12:15 - 12:45
    This talk will give an introduction to neural networks and how they are used for machine translation. The primary goal of the talk is to provide a deep enough understanding of NMT that so that the audience can appreciate the strengths of weaknesses of the technology. The talk starts with a brief introduction to standard feed-forward neural networks (what they are, how they work, and how they are trained), this is followed by an introduction to word-embeddings (vector representations of words) and then we introduce recurrent neural networks. Once these fundamentals have been introduced we then focus in on the components of a standard neural-machine translation architecture, namely: encoder networks, decoder language models, and the encoder-decoder architecture.

  • 13:45 - 14:15
    At first sight, forecasting looks like another regression problem; however, time series pose unique statistical challenges that require specialised models. Starting with some common mistakes (and fixes!) in time series analysis, we will then introduce an array of techniques from classical ARIMA to neural networks, with a short Bayesian detour. Different methods will be illustrated and compared using a large spatio-temporal dataset as motivating example. We conclude with some modelling recommendations and strategies to tackle general forecasting problems.

  • 14:15 - 14:45
    Reinforcement Learning is learning what to do – what action to take in a specific situation – in order to maximize some type of reward. It’s one of the most promising areas of Machine Learning today. It plays an important part in some very high-profile success stories of AI, such as mastering Go, learning to play computer games, autonomous driving, autonomous stock trading, and more. In this talk we’ll introduce the main theoretical and practical aspects of Reinforcement Learning, discuss its very distinctive set of challenges, and explore what the future looks like for self-training machines.

  • 15:00 - 15:30
    User satisfaction surveys are a common and powerful tool in helping customer experience teams improve their product, by helping them understand which parts of the user experience contribute most to a given outcome. However, they suffer from two disadvantages: first, it is difficult and time-consuming to design good survey questions and to analyze results, and second, convincing many users to complete multi-page, monotonous surveys is difficult and a bad user experience. In this talk, we explore techniques such as clustering, natural language understanding, and summarization in order to enable customer experience teams easily derive insight from a single open-ended question rather than a long sequence of very specific multiple-choice questions.

  • 15:30 - 16:00
    Deep Learning is the buzzword of the day in IT. Fueled by the significant advancements generated by GPUs and lately by FPGAs, deep learning is on the path of becoming ubiquitous. Yet most people are unaware of the fact that the first incarnation of a neural net, the perceptron, has its 60th birthday this year. Once almost deemed as a “dead end”, neural nets, represented by their most preeminent incarnation – the deep learning nets, are coming back into the public spotlight with a vengeance. Join me in this session to discover the inner workings of deep learning networks, their advantages and pitfalls, as well as their areas of applicability. I’ll cover the history and evolution of the field as well as its present state of the art. We’ll talk about the most popular deep learning platforms as well as about how the cloud and the intelligence edge enable together a broad range of scenarios to be addressed.

  • 16:15 - 16:45
    Azure is huge – there are some many choices to make and new options seem to arrive every day. But which to chose? And why? In this session we will explore the various options of doing Artificial Intelligence on Azure and also do a demo of the latest and greatest technology available for you to use today. Even a sneak peak into the future will be provided.




Chopin Hall - Palas Congress Hall, Palas Street no. 7A, Iași, Romania 700259