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i2cinc
Data Scientist
June 29, 2026 – Present
GithubActionsTutorialProject
November 11, 2024 – November 12, 2024
Flask app showcasing CI/CD with GitHub Actions. It includes automated testing with pytest and Docker workflows to build, test, and deploy the app to DockerHub.
View ProjectPytorch_Implementations
March 16, 2024 – April 2, 2024
This repo contains various implementations of Deep Learning models using pytorch.
View ProjectChatBot-HugChat
May 12, 2023 – May 12, 2023
Streamlit powered ChatBot Using Hug Chat API.
View ProjectStreamlit-Iris-Classification-App
April 3, 2023 – April 7, 2023
This is a web application that classifies iris flowers based on their sepal length, sepal width, petal length, and petal width. The app is built using Streamlit and the classification model is trained using Jupyter notebook.
View Projectcifar10-image-recognition
March 25, 2023 – April 7, 2023
This is a CNN project in Python that classifies images from the Cifar10 dataset. The model used is ResNet-50, which has been trained on the dataset and saved as "resnet.h5" file. A Streamlit app has been created to load the model and predict the class of an image uploaded by the user.
View ProjectModel-Based-Movie-Recommendation-System
February 27, 2023 – April 7, 2023
This Notebook Recommends Movies by finding correlation based on user rating of each movie
View ProjectClassification-Based-Recommendation-System
February 27, 2023 – February 27, 2023
This Notebook Recommends whether a user will be able to pay back loan or not. This system could be used by banks before giving loans to costumers
View ProjectPopularity-Based-Restaurant-Recommendation
February 26, 2023 – February 26, 2023
This Notebook Recommends Restaurants based on popularity
View ProjectSnake-Game-Python
February 20, 2023 – April 7, 2023
A snake game using python turtle graphics
View ProjectWaffer_Fault_Detection
July 20, 2022 – March 29, 2023
The Waffer Fault Detection project in Python involves using machine learning algorithms to detect and classify defects on silicon waffers in semiconductor manufacturing.
View ProjectCultural Fit Analysis
The candidate's projects show a strong focus on machine learning and data science applications, which aligns well with a Data Scientist role. The diversity of projects (fault detection, chatbots, recommendation systems, image recognition) indicates a broad interest within the field. However, all projects are personal, limiting insight into collaborative work or contributions to larger organizational goals. The single listed professional experience as 'Data Scientist' is current with no start date, making it difficult to assess actual professional contributions or cultural alignment within a team.
Soft Skills & Operational Fit
Insufficient data to assess soft skills and operational fit. The candidate's project descriptions indicate an ability to work on self-directed projects, but collaboration, problem-solving under pressure, and communication in a team setting cannot be evaluated.