The biggest European conference about ML AI and Deep Learning applications
running in person in Prague and online.

Machine Learning Prague 2022

In cooperation with

, 2022


World class expertise and practical content packed in 3 days!

You can look forward to an excellent lineup of 45 international experts in ML and AI business and academic applications at ML Prague 2022. They will present advanced practical talks, hands-on workshops and other forms of interactive content to you.

Stay tuned. We will publish our full program with talks and 1-day, hands-on workshops soon!

What to expect

  • 500+ Attendees
  • 3 Days
  • 45 Speakers
  • 8 Workshops
  • 2 Parties

Phenomenal First speakers announced

Radovan Kavicky

Principal Data Scientist & President, GapData Institute

Radovan Kavicky joined Datacamp among its first employees (historically 1st Data Science Instructor from CEE region & is still historically the only one worldwide who have made successful transition from regular student to instructor and employee after being #1 worldwide @ Datacamp platform for nearly a year, back in 2017).

Radovan is Data Science Polyglot (R, Python, Julia ++more) and Data Science Veteran with over 10 years of experience in Data Science and Applied AI/ML Consulting & extensive knowledge in the area (Data Science consulting, education & community building with successful cooperation with global leaders within our industry, like f.e., Anaconda or Tableau). Radovan is also co-founder of Slovak.AI (Slovak Research Center for Artificial Intelligence) and member of various international professional societies within our Data Science & AI/ML industry, like f.e. IEEE Computer Society, CLAIRE (Confederation of Laboratories for Artificial Intelligence Research in Europe), European AI Alliance (European Commission/Futurium), TAILOR network (Trustworthy AI - Integrating Learning, Optimisation and Reasoning), UDSC (United Data Science Communities), PyData Global Network, Global Tableau #DataLeader network & The Python Software Foundation (PSF).

Radovan is also Founder of PyData Slovakia/Bratislava (#PyDataSK #PyDataBA), R <- Slovakia (#RSlovakia), Julia Users Group Slovakia (#JUGSlovakia), SK/CZ Tableau User Group (#skczTUG) & Effective Altruism Slovakia (#EASlovakia) that you are all welcome to join.

Practical & Inspiring Program


at CEVRO Institut, Jungmannova 28/17, Prague 1 (workshops won't be streamed)


Room 103 Room 106 Room 203 Room 205
coffee break

Text analysis with Apache Spark 3.x and Python

Room 103

David Vrba, Emplifi

Apache Spark became a standard for data processing in a big data environment. It is well integrated with the Python programming language and the integration became even more emphasized in the 3.x releases. In this hands-on workshop we will see how Spark can be used for analyzing textual data using Spark SQL along with the native package for machine learning - Spark ML. We will also explore Spark NLP which is a state-of-the-art library for natural language processing that provides machine learning and deep learning capabilities for text analysis on top of Spark.

Language Model Essentials: Pre-training, Metrics, and Community

Room 106

Nick Doiron, Hewlett Packard Enterprise

Learn the essentials to train fine-tune and patch language models with the Transformers library. In this workshop we will compare accuracy of masked language models on select tasks using architectures such as BERT and T5. For generative models (such as GPT-2) we explore the options to generate text through greedy search and beam search. In the end we will cover how to participate in the open source NLP community including sharing language models on HuggingFace and/or AdapterHub.

Synthetic Data Generation for Computer Vision

Room 203

Frederick Bednar, EBCONT
Julian-Thomas Erdödy, EBCONT
Clifford Bednar, EBCONT

Collecting reliable and properly labeled image and video data in sufficient quantities denotes one of the major challenges in computer vision still preventing many projects both in research and industrial domains from seeing the light of day. In this workshop we would like to show you how to generate and use synthetic datasets with the help of game engines in order to accelerate the image annotation process. We will augment our datasets using domain randomization techniques to simulate possible variations and scenarios in the real data. Finally we will use these datasets to train a neural network and demonstrate the benefit of this approach by measuring the network’s performance against real data.

ML in live data processing

Room 205

Tomáš Neubauer, Quix
Javier Blanco Cordero, Quix

In this workshop you will learn how to use machine learning in real-time systems. You will process data live with a trained ML model with almost no latency. In 3 hour workshop you will get a chance to build PoC using Python from scratch with a team that worked in F1 racing processing car telemetry at a massive scale.

coffee break

Recommendation systems and user representations

Room 103

Radek Tomšů,
Václav Blahut,
Tomáš Nováčik,
Adam Jurčík,

Popularity of deep neural networks and embeddings in machine learning is transcending into the realm of recommender systems and is getting attraction within industry. Recommendation systems are used in many industries such as eCommerce social networks content providers and many more. They are improving user experience radically. In the theoretical part of the workshop we will go through different architectures of neural networks that are currently the state of the art in the recommendation domain. In the practical part we will train deep neural networks on our internal datasets and demonstrate benefits of various architectures and user features. In particular we will show how to employ a variety of user features to address the cold-start problem.

Explainable AI/ML (XAI) in Python

Room 106

Radovan Kavicky, GapData Institute

In this workshop led by Radovan Kavicky from Datacamp &amp; GapData Institute you will get familiar with Explainable AI (XAI) and how to implement these principles in Python. Together we will open the "black box" of machine learning where sometimes even its designers cannot fully explain why an AI/ML arrived at a specific decision and also point out differences from statistical learning. We will learn how to better design systems that imitate intelligence in transparent way and you will also get an overview of current trends in Explainable AI/ML.

Reverse Image Search

Room 203

Jan Rus, Emplifi
Peter Jung, Emplifi

Find most similar images in the data given a reference image. We start with a simple baseline using ImageHash. Then show its limitations and proceed to a more robust solution using the latest DL models. With an adjustable threshold specifying how big differences are allowed. Along with fixes for edge-cases like completely black or white images.

Practical aspects of reinforcement learning deployment in business

Room 205

Michal Kubišta,
Petr Stanislav,

Reinforcement learning models are a new type of intelligent machine that can help you drive your car or beat you in Starcraft. Let’s say you have successfully trained your model and it works on your machine. Now how do you make it useful to your colleagues? We will of course walk you through the process of building and training such models but our work(shop) will not stop there. How do we tune the hyperparameters? How can we deploy our solutions so other people can use them (get over the phrase “it works on my PC”)? How do we monitor the performance and compare different approaches? These problems can be as complex as building a deep neural network and cause many projects to fail before ever reaching the production stage. And that’s what we want to focus on.



La Fabrika, Komunardů 30, Praha 7 (and on-line)

To be announced

Conference day 1

La Fabrika, Komunardů 30, Praha 7 (and on-line)

To be announced

Have a great time Prague, the city that never sleeps

You can feel centuries of history at every corner in this unique capital. We'll invite you to get a taste of our best pivo (that’s beer in Czech) and then bring you back to the present day to party at one of the local clubs all night long!


Venue ML Prague 2022 will run hybrid, in person and online!

We are happy to announce that ML Prague is back as an in-person event in 2022. The main conference will be held at La Fabrika while our workshops will take place at CEVRO Institute. After 3 years, we can finally enjoy the conference together in one place.

We will also livestream the talks for all those participants who prefer to attend the conference online. Our platform will allow interaction with speakers and other participants too. Workshops require intensive interaction and won't be streamed.

Conference Hall

La Fabrika
Komunardů 30, Praha 7


CEVRO Institut
Jungmannova 28/17, Prague 1

Now or never Tickets

Early Bird

Sold Out

  • Conference days € 195
  • Only workshops € 150
  • Conference + workshops € 330

Standard Ticket

Late Ticket

Last 100 tickets

  • Conference days € 280
  • Only workshops € 195
  • Conference + workshops € 450

What You Get

  • Practical and advanced level talks led by top experts
  • 2 parties in the city with people from around the world. Let’s go wild!
  • Delicious food and snacks throughout the conference

They’re among us We are in The ML Revolution age

Machines can learn. Incredibly fast. Faster than you. They are getting smarter and smarter every single day, changing the world we’re living in, our business and our life. The artificial intelligence revolution is here. Come, learn and make this threat your biggest advantage.

Our Attendees What they say about ML Prague

Thank you to Our Partners

Co-organizing Partner

Platinum Partners

Gold partners

Would you like to present your brand to 500+ Machine Learning enthusiasts? Send us an email at to find out how to become a ML Prague 2022 partner.

Become a partner

Happy to help Contact

If you have any questions about Machine Learning Prague, please e-mail us at


Jiří Materna
Scientific program & Co-Founder

Teresa Caklova
Event production

Alena Osipova

Jona Azizaj
Communities and partnerships

Gonzalo V. Fernández

Natalija Slavkovska
Social media