Paes, B.
B.ASc. degree in Information Systems. Has keen interest in bio-inspired neural computing, computational physics, geostatistics and pattern recognition. Strong background in areas as: machine learning, deep learning, computer vision and, through data science techniques, pattern recognition in complex datasets. Seeking to automate and extract data from the vast majority of personal tasks.
Supported by:
Python
Data Science and AI | |
Data Automation | requests, beautifulSoup, selenium and others |
Data Analysis and Processing | pandas, numpy, bqplot, matplotlib and seaborn |
Data Augmentation | open-cv and numpy |
Machine Learning | bayesian learn, k-nn, k-means, random forest, svm and others |
Deep Learning | neural nets, gans and convnets |
Python
Dev | |
Web Frameworks | bootstrap, django and flask |
Microservices | airflow, jenkins and pytest |
R
Data Science and AI | |
Data Analysis and Processing | built-in packages |
Machine Learning | k-nn, k-means, random forest and others |
Julia
Data Science | |
Data Analysis and Processing | built-in packages |
SQL Databases
Data Manipulation | |
DQL | select |
DDL | create, drop and alter |
DML | insert, update and delete |
NoSQL Databases
Data Manipulation | |
MongoDB | |
Cassandra |
Cloud Computing
Data and Process Automation | |
Azure | Virtual Machines and Machine Learning APIs |
AWS | EC2, Lambda and Machine Learning APIs |
GCP | BigQuery, Data Flow and Machine Learning APIs |
IBM Cloud | Watson Services |
Curriculum Lattes
http://lattes.cnpq.br/5724163564352003