Discover the business application of Machine Learning taught by experts from the private sector!
Welcome to the intro page of the Machine Learning Section of the Central European Conference. If you join us, you will meet with the ML tecniques and will be able to apply it in a data science project.
Why should you apply?
The terms Deep Learning, Artificial Intelligence and Machine Learning (ML) became buzzwords in the past 10 years but only a few have solid grasp of the concepts behind it. In several news and articles, they are mistakenly used interchangeably however they have different meaning and assumes different knowledge for the users to deeply understand their methods. ML techniques were originally used in different fields of academia but quickly became a powerful tool for companies to improve business, provide for better customer experience and generate operational efficiencies. This section is designed to introduce participants to basic ML techniques and provide them with useful insights into how companies capitalize on them.
Why should you participate?
In a nutshell: you’ll have a very exciting vacation in Budapest, where you’ll get to explore the city while uncovering the future of Business with excellent presenters and fellow students.
Who can participate? For our requirements, scroll down to the bottom of the page, to the “Requirements and Application” section.
Knowledge strategy in the time of artificial intelligence
Algorithms vs. Experts
Race between fortune-tellers – Human vs. machine predictions
How to sell your analytics result to the decision-makers?
Case study II.
How to Cluster a Dataset
How to do Graph Analytics
András Kárpáti, Senior Data Scientist at Lynx Analytics
Mór Kapronczay, Data Scientist at Starschema Ltd.
Requirements and application
1. Your CV
2. Motivation letter (focusing on the following questions: What is your motivation for applying for this section? What is your expectation regarding the course? – learning outcomes, hands on experience etc.)
3. Your most recent work in English that you are proud of and took at least 10 working hours to finish (can be a github repository, your thesis, a research paper or codes)
4. Rate your skills on a scale from 1 to 5
b. Business studies
Thanks for reading throught the page! We’ll hopefully meet at the masterclass 🙂