Abdolkarim Saeedi

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Self-taught Machine Learning Engineer.
Practical knowledge with many popular algorithms in the most efficient frameworks namely Tensorflow, Keras, Sci-kit, OpenCV learn and Scipy.
Love reading papers and articles on new ML advancements whenever there is a chance.
High desire to solve complex problems and optimize existing models, not just when at work.
Writer and programmer in a number of computer aided diagnosis  and image processing based studies.
Proficient with python standard library and best practices.
Vast experience in Ensemble learning meta algorithms and competitive ML frameworks like XGBoost, LightGBM and CatBoost.
Ability to deal with all kinds of data: Videos, Images, Time-Series, Text and Structured.
Talented in applying developing real time algorithms in Restful services.
The ability to train deep learning models in a fast pace using google colaboratory.
Familiarity with writing the majority of SOTA complex deep learning blocks such as ResNet, Xception, Inception, DenseNet and etc.
Professional in darknet YOLO training and transfer learning for object detection purposes.
Expertise in advanced Face Recognition and Metrics with OpenCV, DLIB and InsightFace.
Necessary skills to leverage more system power using CUDA, CUDNN and concurrent computations .
Highly efficient with filtering, linear and non-linear feature extraction and dimensionality reduction in signal and image processing.
Proficient in web server development with Flask, FastAPi and jinja2, familiar with Django.
Capability to use ARM based boards such as RPI and asus tinker board effectively for surveillance integration.
Linux and windows server programming experience.
Knowledge in designing GUIs with Tkinter.
Highly skilled in Database Management using MongoEngine, SQL.
Familiarity with android development and java.
Electrical Engineering and Biomedical domain knowledge with Master's degree focused in Biomedical/Medical Engineering from Islamic Azad University, Science And Research Branch.