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maringá, brazil
It's currently 8:59 AM here
Joined July 3, 2017
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Ricardo C.
@ricacorassa
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maringá, brazil
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Software Engineer
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Experience
Software Engineer
Mar 2017 - Present
I'm focused on developing solutions with Watson, Machine Learning, Cognitive Computing and Statistics.
* Technical skills *
• IBM Bluemix (Softlayer Infrastructure, Docker, Kubernets, IBM API's)
• Javascript (NodeJS)
• DevOps
• Watson Developer Cloud
• IBM Data Science Experience
• IBM SPSS
• Product developer
* Humans skills *
• Teamwork with diversified and complementary skills
• Research and innovation
Software Engineering and Co Founder
Jan 2016 - Mar 2017 (1 year, 2 months)
Cognativa was a Start-up that was active in the development of solutions in Data Mining, Business Intelligence and Business Analytics.
* Technical skills *
• IBM SPSS Modeler
• IBM Bluemix
• R
• Weka
• Java development
* Human skills *
• Project leadership
• Team building
• Product development and communication
• Communication with professionals of different nationalities.
Scientific research, development and innovation
Aug 2015 - Aug 2016 (1 year)
Since August 2015, I have received a research grant attributed by the Brazilian gouvernment (CNPq). I have been developping processes related to machine learning, and specifically with the process of recognition through styles or emotions.
• Study of the hierachical classification
• Study of the process on musical emotion classification
• Application of the hierarchy approach on the musical emotion classification
Education
Computer Engineering
(6 years)
Academic exchange - Generalist engineering
(Less than a year)
Training in French
(Less than a year)
Qualifications
The Data Scientist’s Toolbox
Coursera
2016
The Data Scientist’s Toolbox an online non-credit course authorized by Johns Hopkins University and offered through Coursera
R Programming
Coursera
2016
R Programming an online non-credit course authorized by Johns Hopkins University and offered through Coursera.
Getting and Cleaning Data
Coursera
2017
Getting and Cleaning Data an online non-credit course authorized by Johns Hopkins University and offered through Coursera.
Publications
Automatic Musical Genre Classification of Chords of Music
14° Brazilian Symposium of Musical Computation
For the task of automatic music genre classification the use of content-based features appears to have reached a glass-ceiling. For this reason, recent research in music genre classification has been working on developing new approaches for the task. In this paper we present five novel feature descriptiors based on "cifras" (a document that contains the harmonic structure and progression of the songs).
http://compmus.ime.usp.br/sbcm/2013/pt/artigos_aceitos.html
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