Position: Python Developer
Category: Python
English level: upper
Years of experience: 0

Created ml model for handwritten characters recognition using simple neural network with decent accuracy.
Model for handwritten character recognition (A-Z and 0-9). Datased used for training contained handwritten english alphabets and numbers images in size 28*28 pixels. Images are stored as Gray-level Pixel values are in range from 0 to 255 which represents the intensity of each pixel in the image and they are normalized to represent value between 0 and 1. Neural network contains 1 flatten level, 144 node input level, 72 node hidden level and 36 node output level.

Model loss and accuracy data with train data: loss: 0.0817 - accuracy: 0.9726

Model loss and accuracy data with test data: loss: 0.1509 - accuracy: 0.9589
Created personal blog and meetups web sites projects while taking the course on Python/Django.
Also created handwritten characters recognition project using tensorflow, scikit-learn and opencv.
All projects available on my github account.