Data Engineer
Summary
Hot Zone and Hot Cell Analysis for Peer-to-Peer Taxicab Firm
Created a list of entries on spark platform with a most count of occurrences by applying aggregate count operations to 2-
dimensional dataset points and rectangles (Hot Zone Analysis).
Implemented Hot-Cell Analysis on Getis - Ord Statistic Of New York City Taxi Trip data sets of huge volume to find a geographical
point of taxi activity with 97.27% Accuracy.
Classification Using Neural Networks & Deep Learning May 2021
Implemented Classification task on SVHN dataset with 75k+ house plate pictures data samples by building and training
Convolutional Neural Network by using Keras and TensorFlow.
Trained the network with an SGD optimizer with different learning rates starting with 0.02.
Achieved the Test Accuracy: 91.65% and Test Loss of: 28.6%.
Diffie Hellman and Encryption Project
Hands-on D-H protocol & number theory concepts to solve real-world problems.
Implemented Diffie Hellman key exchanging protocol by generating the 256-bit key using AES (Advanced Standard Encryption) or
Rijndael encryption.
After Key calculation implemented a program that performs encryption of the plaintext string and decryption of given ciphertext
bytes.
Expectations
Learning the tasks at my own pace with a healthy environment where ideas can be shared and problems can be solved by discussing, a project group that believes in peer-to-peer helping nature. Scope of learning new things regarding new technologies.
Employment Preferences
Expected Base Salary
**0,000 USD / year
