This event is cancelled

The Global AI On Tour in Bucharest, Romania is a free event on 22 May 2020 from 09:00 - 18:00.

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About the event

Join the Bucharest edition of Global AI Community on Tour for hands-on sessions in applied Machine Learning. From beginner to advanced workshops, we'll cover five different applications in one engaging day packed with information on Azure Machine Learning and more.


9:00 Welcome coffee


9:30 Enhance Your Corporate Competitiveness by Leveraging AI (45 min)

Speaker: Daniel Jinga, Consulting Director, Softelligence


10:15 Word Embedding (90 min)

Trainer: Alexandru Petrescu, Microsoft AI MVP

Learning objectives:

  1. Seeing how an automatic learning algorithm "understands" strings

  2. Exploring several methods for word embedding

  3. Comparing methods to identify advantages and disadvantages


11:45 SQL Server and Machine Learning introduction (90 min)

Trainer: Cristian Lefter, Independent Trainer, DTM, MCT, SQL MVP 2005-2018

In this workshop we will learn about Python integration by building and deploying a Python-based machine learning solution on SQL Server. We will use T-SQL, SQL Server Management Studio, and a database engine instance with Machine Learning Services and Python language support. The workshop assumes familiarity with basic database operations such as creating databases and tables, importing data, and writing SQL queries.


13:15 Lunch break (30 min)


13:45 Workshop 3 – TBC (90 min)

Trainer: Sorin Peste, Cloud Solution Architect, Microsoft


15:15 AI-enabled damage assessment on cars: using computer vision and deep learning to streamline damage detection in motor claims (120 min)

Trainers: Laurentiu Diaconu, Advanced Analytics Leader, Softelligence; Tudor Popa Data Scientist, Softelligence

Learning objectives:

  1. Understand Computer Vision applicability in Insurance

  2. Explore state-of-the-art Object Detection architectures

  3. Use pre-trained TensorFlow models that understand whether objects are present in images

  4. Build your own TensorFlow models to assess car damage using the TensorFlow Object Detection API

  5. Evaluate different models and deploy for near real-time inference


17:15 Call-center Workload Forecasting using Azure ML Studio (60 min)

Trainer: George Schiopu, Data Visualisation Consultant, Softelligence

Learning objectives:

  1. Timeseries forecasting using both seasonal and non seasonal methods.

  2. Generate accuracy metrics & compare results.

This workshop assumes beginner knowledge of R and Python scripting.


18:15 End



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