MK

Hourly rate: members only

Availability: members only

Willingness to travel: At home

Professional status: Employee

Last updated: 16 Jan 2022

Total work experience: 2 year(s)

Language skills: English,

Personal summary

A versatile, results-driven professional. Dedicating academic and industry knowledge to the fields of Deep Learning, Data Science and Computer Vision. I hold expert in depth knowledge of supervised and unsupervised deep learning techniques. During my MSc, I have built several deep learning models for the diagnostic classification of breast/ skin cancer with excellent performance. I have also designed and implemented different deep learning classification and regression analysis techniques for the accurate prediction of Spotify song attributes (genre, liveness etc). I then proceeded to build Natural Language Processing deep learning models for text recognition using a combination of GRU and LSTM bidirectional models. During my dissertation I have collaborated with an industry partner for the development of advanced-modelling techniques of wind farm energy data. Since my graduation, I have been working on the field of Computer Vision focusing on training and implementation of state of art deep convolution networks (Yolo , RestNet etc) for accurate real time classification and segmentation analysis (Fast-RCNN, YoloAct), for efficient crowd measurement applications.

Skills