From Zero to Natural Language Processing Hero

Ever wondered how your email identifies spam messages? How does news applications classify news into topics? Or how does Google translate detect the language of a page? In this session we will explore the theory foundations behind natural language processing. Then we will, step by step, build a machine learning solution that automatically classifies text messages. 

Tarek Amr


Senior Machine Learning Scientist

Tarek Amr is a Senior Machine Learning Scientist at Adyen. Before Adyen, Tarek worked for marketplaces such as Catawiki and TicketSwap, where he built end-to-end data solutions and predictive models. Tarek has published a couple of books on machine learning and data visualization. His most recent book is “Hands-On Machine Learning with Scikit-Learn and Scientific Python Toolkits”. Tarek holds an MSc. in Computer Science from the University of East Anglia, with focus on algorithms, information retrieval and natural language processing.

What the attendees will learn

Attendees will learn how to prepare their textual data for machine learning models to use. They will also see how the different representations of the data impacts the downstream algorithms used. They will learn the theory behind the algorithms we are going to use, and how to compare their performance.  


A laptop and no prerequisite knowledge of machine learning is needed, but a basic understanding of Python programming is required.

Companies using this technology

Natural language processing it is used in all sort of companies, from global search engines such as Google and Bing, to social media platforms and email providers to researchers analysing surveys and web content. 

Workshop Plan

We will start by setting the needed environment on your machines. 

After that there will be a mixture of theoretical information and practical hands-on. 

During the hands-on part, the attendees will get access to the data and try things themselves. 

From Zero to Natural Language Processing Hero

Date and time:

Wednesday 27th

09:00 - 14:00


NPS, Machine Learning, Python

Target audience roles:

Developers and Data Scientists




Coffee and tea

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