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$20 USD / hour
Flag of POLAND
siedlce, poland
$20 USD / hour
It's currently 10:47 PM here
Joined July 23, 2013
0 Recommendations

Patryk S.

@PatrykSkowron

5.0 (6 reviews)
3.2
3.2
100%
100%
$20 USD / hour
Flag of POLAND
siedlce, poland
$20 USD / hour
100%
Jobs Completed
100%
On Budget
100%
On Time
50%
Repeat Hire Rate

Deep Learning engineer with expertise in NLP

Industry experience to work with large sets of text data for Natural Language Processing. Skills: scrap, crawl and integrate high quality data. Build rapid prototypes of Machine Learning models - both classic and Deep Learning. Proud of: Designing a system that crawls the Web, process content, store it in Database, and evaluate Machine Learning models in loop. Motivation: take responsibility for resolving problems and delivering high quality solutions. Learning new concepts. Simplifying complex ideas and implementing them. Tools: Unix Shell (with built-in tools like grep), Python (nltk, regular expressions, Pandas, scikit-learn, Tensorflow), Java, mongoDB, Git. I am fluent in English. I speak and understand basic Spanish too. I am familiar also with: Hadoop ecosystem (Spark and RDD) and Nutch (open source data crawling tool).

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Portfolio

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Reviews

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Showing 1 - 5 out of 6 reviews
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5.0
€50.00 EUR
good job
R Programming Language
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Flag of Alexander P.
@omniphon
10 years ago
5.0
$50.00 USD
Patrick has proven his good skills in mathematics and Matlab programming. I apprecite for this.
Data Processing
Matlab and Mathematica
Statistics
Mathematics
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Flag of Ievgen G.
@Zhats
10 years ago
5.0
$70.00 USD
Again good working experience with Patrick.
Matlab and Mathematica
Statistics
C++ Programming
Mathematics
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Flag of Ievgen G.
@Zhats
10 years ago
5.0
$55.00 USD
Patrick is nice and dedicated person. I recommend him for everyone.
Matlab and Mathematica
Statistics
C++ Programming
Mathematics
User Avatar
Flag of Ievgen G.
@Zhats
11 years ago
5.0
$50.00 USD
Patrick is great worker. I'm always happy with his work and recommend him to anyone.
Matlab and Mathematica
Statistics
Mathematics
R Programming Language
User Avatar
Flag of Ievgen G.
@Zhats
11 years ago

Experience

Natural Language Processing Engineer

Samsung Research and Development Center
Jun 2017 - Present
During one year of work full of passion, I've learned how to obtain (crawling, scrapping, HTML extraction) big amount of data from various sources (web pages, JSONs, mongoDB), integrate them into datasets, train and evaluate machine learning models. I am proficient in Python to write scripts and smaller systems that are optimized, highly readible and ready-to-reuse in other projects. tools for ML: Tensorflow, Keras, Pandas, scikit-learn

Data Mining Specialist

Algolytics
Sep 2015 - May 2017 (1 year, 8 months)
Writing advanced scripts in order to automate tasks (Python, SAS, SQL) Participating in analytical projects for clients in telecom industry: Building scoring models (e.g. churn / monetization models) Streaming media industry: Preparing customer behavioral segmentation models Designing and Building 360 Degrees Data Mart

President and active member of academic organisation

Soli Deo
Oct 2010 - Jun 2015 (4 years, 8 months)
Organising work of the unit at Warsaw University of Technology as a president. Participating and coordinating conferences, events, actions. Taking care of new members of association as a head of human resources.

Education

Master in Applied Physics (Complex systems modelling)

Politechnika Warszawska, Poland 2014 - 2015
(1 year)

Erasmus exchange (engineer studies)

Université Bordeaux I, France 2013 - 2014
(1 year)

Engineer in Computational Physics

Politechnika Warszawska, Poland 2010 - 2014
(4 years)

Qualifications

Design Thinking Course

Design Thinking Warsaw organisation
2013
Completed course of Design Thinking - methodology for practical, creative resolution of problems or issues that looks for an improved future result.

Publications

Master thesis: Crises modelling in the World Trade Web

Minimum spanning tree of World Trade Web

Warsaw University of Technology
In the paper analysis of undirected weighted graphs which represent the world trade web in years 1950-2000 has been performed. Nodes indicate countries. Edges represent trade connections between countries. To every edge weight is assigned. This weight corresponds to trade volume. This analysis allows one to identify the most important trade channels. In the paper this thesis is confirmed. It was achieved using transformation of network to minimum spanning tree which imitates its backbone. Firstly, ana

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