🚀 Full Stack Data Scientist pioneering advanced solutions in AI & ML, driven by a passion for impactful, data-driven innovations and seamless user experiences.
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A00463485_PythonAssignment_DataMining
April 12, 2024 – April 12, 2024
A00463485_PythonAssignment_DataMining — GitHub repository
View ProjectCanada_Sales_Data_Analysis
April 10, 2024 – April 10, 2024
This is the dashboard created for Canada Sales Data
View ProjectMovie-Reviews-Sentiment-Analysis
March 1, 2024 – March 1, 2024
The main goal of my project was to perform sentiment analysis on the IMDb dataset to classify movie reviews as positive or negative.
View ProjectBanknote_Authentication
February 29, 2024 – March 1, 2024
This repository contains code and analysis for a machine learning assignment focused on the Banknote Authentication dataset. The project aims to build and compare logistic regression and neural network models for classifying banknote authenticity.
View Projectnsrentals
February 15, 2024 – July 7, 2024
Develop a centralized platform to access and analyze up-to-date market rental rates for properties and parking within the Halifax Regional Municipality.
View ProjectTransformers_TB
January 18, 2024 – January 20, 2024
Developed a whole transformer from using pytorch library including its encoder and decoder part. Used layers of encoder to reverse a list of integer.
View ProjectPythonAssignment_A00463485
December 11, 2023 – December 15, 2023
PythonAssignment_A00463485 — GitHub repository
View ProjectMatchMaking_MCDA
November 8, 2023 – November 9, 2023
Matching the people with similar interest with each other from MCDA class.
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards data science and machine learning, aligning with the target role. The diversity of projects (e.g., market rental analysis, matchmaking, sentiment analysis, banknote authentication, transformers) indicates a broad interest in applying data science techniques to different problems. However, all projects are personal, which might suggest a lack of experience in collaborative or production environments. The absence of professional experience or education details makes it difficult to fully assess cultural fit within a team or corporate structure.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. No psychometric test results or interview feedback provided.