ई-रोजगार

Department of Employment, Chhattisgarh

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श्रम सम्मान राशि

Directorate of Treasury Accounts and Pensions, Finance Department, Chhattisgarh

Link

Treasury CG

Directorate of Treasury Accounts and Pensions, Finance Department, Chhattisgarh

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Ekosh Online Chhattisgarh (Website Maintainer)

I am responsible for managing this Ekosh website and New webpages creation of Directorate of Treasury Accounts and Pensions, Finance Department, Chhattisgarh

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Web Development with Python and Flask

Build a webpage using HTML and CSS, connect it with a database and deploy it using Flask Framework.”

Result: The objective of the course project is to apply all the skills & techniques learned during the course to develop a webpage.

Project Link Code

Exploratory Data Analysis - GitHub Repository Analysis

I have selcted some topics like Data-Science, Machine-Learning, Computer-Vision, etc. Then I have fetched most stared 100 repository details including repository commits,issue,fork, etc.

Result: The objective of the course project is to apply all the skills & techniques learned during the course to a real-world dataset. In this project we pick a real-world dataset of github repo dataset and used Numpy & Pandas to parse, clean & analyze data, Matplotlib & Seaborn to create visualizations, Write a blog post to showcase the work.

Project Code Dataset Blog

Data Structures and Algorithms in Python

A beginner-friendly introduction to common data structures (linked lists, stacks, queues, graphs) and algorithms (search, sorting, recursion, dynamic programming) in Python.

Result: Picked a problem from an online source (LeetCode, HackerRank, GeeksForGeeks etc.)Used the problem-solving template to solve the problem step-by-step using the method i've learned in this course. Documented the solution and perform complexity analysis by adding explanations in Jupyter notebook & published it.

Project Code

Age of Death prediction using Linear Regression

Picked a dataset of WHO life expectancy and applied the concepts learned in this course to train deep learning models end-to-end with PyTorch, experimenting with different hyperparameters & metrics. Understand and describe the modeling objective clearly What type of data, type of problem.

Result: Cleaned the data and perform exploratory analysis, defined a model, Train the model, Make predictions on samples, Evaluated on the test dataset, Saved the model weights, Recorded the metrics.

Project Code Dataset

Real-World Machine Learning Model - Photo Quality Prediction

Picked a photo quality prediction dataset from Kaggle.training set contain at least 50,000 rows and 5 columns of data, understand the problem statement and described the modeling objective clearly. Performed exploratory data analysis, gathered insights about the data, performed feature engineering.

Result: Created a training-validation split, and prepare the data for modeling. Trained & evaluated different machine learning models, tune hyperparameters and reduce overfitting to improve the model. Report the final performance of best model, showed sample predictions, and saved model weights.

Project Code Dataset