
Engineer | Biker | Data Scientist
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Ford
Engineer
June 13, 2026 – Present
vision_transformer_tf
December 13, 2022 – January 29, 2023
This repository contains the TensorFlow implementation of the paper "AN IMAGE IS WORTH 16X16 WORDS: TRANSFORMERS FOR IMAGE RECOGNITION AT SCALE" known as vision transformers.
View Projecttransformer-tf
December 1, 2022 – December 6, 2022
This repository contains the code for the paper "Attention Is All You Need" i.e The Transformer.
View Projectpix2pix
March 17, 2021 – March 18, 2021
This project uses a conditional generative adversarial network (cGAN) named Pix2Pix for the Image to image translation task.
View ProjectFace_generation_using_DCGAN
February 28, 2021 – March 31, 2022
Tensorflow 1.x was used to build a DCGAN that is capable of generating fake celebrity faces.
View ProjectSnake_game
February 4, 2021 – February 4, 2021
A simple snake game made with the Pygame module of python.
View ProjectDisaster-Tweets-Classification
August 20, 2020 – August 21, 2020
Real or Not? NLP with Disaster Tweets is a kaggle competition problem where we have to predict which Tweets are about real disasters and which ones are not. I participated in the Kaggle competition and solved the problem using Machine Learning and Natural Language processing. This repository contains all the code regarding the solution that I submitted at that time.
View ProjectCultural Fit Analysis
The candidate's projects are primarily personal and research-oriented, focusing heavily on advanced machine learning and deep learning. This indicates a strong interest in cutting-edge AI/ML development. The inclusion of a simple FastAPI/Docker project suggests some awareness of deployment, but the overall portfolio is heavily skewed towards academic/research implementations. The target role is 'Engineer', which is broad; without more context, it's hard to fully assess cultural fit beyond a strong technical curiosity in AI/ML.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. The candidate's project descriptions are concise, indicating a focus on technical output. No psychometric or English test scores are available.