Bring your notebook and take part in one of 12 AI & NLP related workshops to quickly gain hands-on knowledge on current methods and technologies.
Talk to field experts, scientists and PolEval competition winners to discuss state-of-the-art knowledge in the area of AI and NLP.
Exchange ideas and talk business with participants both from academia and industry.
The schedule of AI & NLP Workshop Day is tentative and may change in the coming weeks.
From hello world to object detection. We are going to go through the simplest Python program that utilizes Tensorflow library, test some models available publicly and finish with working solution for object detection. We are going to see how dataset affects accuracy and how we can improve it. You are going to see some web resources than might be used in this issue and in similar problems. It will be an exciting journey.
The workshop will provide basic information about deep learning: the mechanics behind neural networks, the training procedure (concepts such as backpropagation, RMSProp, Adam, and others), various kinds of neural networks (convolutional, recurrent, autoencoders, GANs, etc.) as well as some tips and tricks for obtaining better performance. We will write code using PyTorch to show these concepts in practice. I will introduce basic features of creating neural networks in PyTorch, using general examples and introducing applications for natural language processing.
In the workshop we will present state-of-the-art techniques for action recognition in videos. We will cover topics such as: video features extraction, features encoding and classification. In practical session participants will prepare and train action recognition model based on Fisher Vector encoding and SVM.
When tackling a machine learning modelling challenge, no matter its specifics, a number of questions could be raised in relation to train and test sets, especially when combined with evaluation results. How to select useful datasets for annotation, as small as possible and as good and efficient as possible as well? How to look into machine learning models and cope with text data? How to show what is the most important for a model? How to debug a machine learning model and find its specific weak points? How to compare two models and understand the difference? We will tell about these challenges and other that we can meet doing data science for big datasets, especially text datasets.
Cloud technology can create numerous benefits for any given company; faster, cheaper, more flexible and easier to keep up to date. These characteristics are essential for companies when data volumes are growing exponentially. In this course, you will learn about cloud-based Big Data solutions such as Amazon S3, Amazon EMR, Azure Data Lake, Azure HDInsight and the rest of the Big Data platforms.
Real time big data analytics is referred to the process of analyzing large volume of data at the moment it is created. It is mostly used in organizations that routinely produce massive amount of data in a very short time. In this workshop, we will learn how to process tweets in real time with tools like Apache Kafka and Apache Spark Streaming.
Serverless ideas, in particular Function as a Service (FaaS), are gaining popularity. A lot has been said about serverless in context of web applications, but not so much when it comes to data engineering and analytics. During the workshop you will learn how to use the serverless approach for data-driven applications for data collection, storage and analytics. The workshop will be based on AWS services but the knowledge is transferable to other systems.
BigData solutions cross our sight in more or less intense way during past couple of years. Various implementations of this technology generate another set of technical skills required when you invest in this field and they may become real road blocks in your projects. When companies work on large analytical solutions Microsoft says: “Stick with T-SQL only when you query Big Data”. You’ll see how efficient can SQL Server be when you retrieve information from less structured files and Hadoop. Plus, how can you mix it with relational databases. SQL Server married with Big Data – live in action!
Workshop will provide basic information from Natural Language Processing (NLP). I will start by explaining what it is and why it is so difficult. Next I will introduce users to basic concepts related to NLP such as tokenization, stemming, POS tagging or sentiment analysis. Together with the participant we go through the Machine Learning methods used in NLP. We end with using Python NLP tools in iPython/Jupyter and some code examples using libraries like NLTK or SpaCy.
Textual Information Retrieval is the activity of obtaining documents/texts relevant to an information need from a collection of documents. Searches can be based on full-text or other content-based indexing as specified keywords. Information retrieval is the science of searching for information in a document, searching for documents themselves, and also searching for metadata that describe data. During the workshop we present elastic as a most popular full-text search engine based on Lucene (it provides a distributed, multitenant-capable full-text search engine with an HTTP web interface), and the set of different supervised and unsupervised methods towards keyphrase extraction as the way of documents indexing in a sparse way.
Fake news is one of the most serious problems in news industry today - false content is used to manipulate public opinion, slander people or just to make money. This is the reason why there is a need to apply automatic methods of detecting such cases. During the workshop we will go through basic as well as more sophisticated machine learning approaches for fake news detection implemented in Python.
The workshop will cover modern sentiment analysis methods with the focus on Polish language. It will discuss available resources and tools, from simple dictionaries to fine-grained, deep learning methods. Tutorial will end with a review of the most recent and interesting advances reported for other languages.
We have a great lineup of speakers from science and business. Here we introduce you to some of them.
Data Science Technology Leader at Findwise
Computer Vision a Research Scientist at Tooploox
Head of Natural Language Processing Laboratory at National Information Processing Institute / Assistant Professor at Warsaw University of Technology
Senior Deep Learning Engineer at Applica / Teaching Assistant at Adam Mickiewicz University
BI Practice Lead at Codec / College Lecturer at Kozminski University
Senior Data Scientist at Applica / Assistant Professor at Warsaw University of Technology
Director of Engineering within the Autonomous Driving Production Unit at TomTom
Big Data Developer / Trainer at Sages
Associate Professor at Warsaw University of Technology / Chief Data Scientist at mBank / Co-founder of Polidea
Ph.D. student in the field of Mathematics at Warsaw University of Technology
Lead Machine Learning Engineer at Sotrender / Data Scientist at SigDelta
Senior Software Specialist at intive
Principal Engineer at Samsung / Assistant Professor at Institute of Computer Science Polish Academy of Sciences
Data Science Section Lead at Findwise
Programmer & Technical Leader at National Information Processing Institute
AI & NLP Workshop Day will take place at Institute of Computer Science Polish Academy of Sciences (5 Jana Kazimierza Str., Warsaw, Poland).
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