Damodar Yadav
@daemonx10
Joined on 12 October 2022
Al/ML Engineer | MERN Developer | Open Source Enthusiast | CS TCET ' 26
GitHub Stats
28
Followers
79
Repositories
1
Organizations
0
Gists
24
Pull Requests
4
Issues
421
Commits
0
Sponsors
2
Contributed To
32
Star Earned
Most Used Languages
98.20%
Jupyter Notebook
1.61%
Python
0.08%
JavaScript
0.04%
HTML
0.02%
TypeScript
0.02%
CSS
0.01%
Shell
0.01%
Cython
Popular Projects
Google-Calendar-MCP-Server
MCP server for Google Calendar integration with AI assistants
TypeScript
2
0
0
0
CEREBUS-AI-CyberShield
AI-Powered Malware Detection: Static, Dynamic, Hybrid Analysis, and Reporting
Jupyter Notebook
2
1
0
0
Sensor-Fault-Detection
The Sensor Fault Detection system is designed to monitor sensors and detect any faults. It uses advanced algorithms to ensure the accuracy and reliability of sensor data.
Jupyter Notebook
2
0
0
0
Machine-Learning
Comprehensive notes and code on Python, data analysis, visualization, machine learning, and deep learning from my AI engineer learning journey.
Jupyter Notebook
2
0
0
3
real_estate_
A full-stack MERN application demonstrating state management with React and Redux. Features include user authentication, CRUD operations, state persistence, and a RESTful API with Express.js and MongoDB for seamless data handling.
JavaScript
2
1
0
0
agriculture-zindi-competition
No description
Jupyter Notebook
1
0
0
0
Top Contributions
Top contributions made by the user in the last year.
Charts
Follow Up
Activity Graph
Contributions Calendar
Contributions made by the user in the last 365 days.
Recent Activity
8/18/2025, 3:06:24 AM
- Time: 23 ms (72.35%), Space: 18.4 MB (29.58%) - LeetHub
8/18/2025, 3:06:23 AM
8/16/2025, 5:21:25 PM
- Time: 0 ms (100%), Space: 17.7 MB (47.05%) - LeetHub
8/16/2025, 5:21:24 PM
8/13/2025, 9:56:17 PM
- Time: 13 ms (36.55%), Space: 18 MB (25.52%) - LeetHub
8/13/2025, 9:56:16 PM
8/13/2025, 2:59:11 AM
8/13/2025, 2:49:44 AM
- Add foundational notes on probability and statistics for ML engineers - Introduced a comprehensive guide on probability concepts, including sample space, events, probability axioms, conditional probability, independence, counting, discrete random variables, PMFs, and expectation. - Included detailed explanations, formulas, properties, and Python examples for practical understanding. - Enhanced the learning resource for ML engineers to build a solid foundation in probability and statistics.
8/12/2025, 12:33:13 AM
- Time: 25 ms (50.53%), Space: 145.1 MB (79.26%) - LeetHub
8/12/2025, 12:33:12 AM
8/10/2025, 11:28:04 PM
- Time: 4 ms (42.37%), Space: 17.9 MB (17.56%) - LeetHub
8/10/2025, 11:28:03 PM
8/9/2025, 6:30:09 PM
- Time: 0 ms (100%), Space: 17.7 MB (55.48%) - LeetHub
8/9/2025, 6:29:01 PM
- Time: 0 ms (100%), Space: 17.9 MB (13.31%) - LeetHub