I participated in two projects. The first involving the largest credit analysis company in Latin America with elements of big data. And the second with the largest television broadcaster in Latin America, involving migration between data and content between servers. All using Python as the main language
- Serasa Experian project using Big Data tools like pySpark and Hadoop to check the score, based on previously trained neural network models
- Globo.com project project using Python (web scraper + Flask + Django) for data communication between platforms
(Networking monitoring position using Python and Linux)
- Use of SNMP protocol for network monitoring. Itaúmon project of Itaú Bank (biggest bank in Brasil) to monitor and control all active points of the network using multi-thread discovering.
- Creation of Machine Learning algorithms to detect fraud and network attacks.
- Implementation of multiple Docker containers in micro services.
- Creation of convolutional neural networks models for forest fire detection. Networks made using OpenCV for initial frame filtering and Keras classification (Tensorflow backend).
- Use of Flask and FastAPI to create fire detection APIs. Solution integrated in the modules of customer monitoring cameras.
- Management of trainee learning activities.
● Preventive basic penetration tests in internal web applications and server services
exposed on the internet.
● Development in Java (object oriented) back end. Integration of machine learning services
with legacy structure.
● Development in Python related to the capture of images by monitoring cameras with the
use of machine learning with the Tensorflow (Google) and OpenCV (NVIDIA) libraries for
recognition and detection of objects in images and video streams.
● Choice of features and configuration of neural networks using the scikit-learn library to
classification and regression of data behaviors using previous information collected.
● Use of Python and Shell Script to optimize access to client servers and
irregularities in services