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Arpit Sengar
Ghaziabad, India
Junior ML Engineer @Omdena || Operational Manager @AI CLUB || Sophomore @VIT Bhopal || Machine Learning Enthusiast || Python Developer || Passionate about Computer Vision
CodersRank Score
What is this?
This represents your current experience. It calculates by analyzing your connected repositories. By measuring your skills by your code, we are creating the ranking, so you can know how good are you comparing to another developers and what you have to improve to be better
Information on how to increase score and ranking details you can find in this blog post.
1,299.9
CodersRank Rank
Top 1%
Based on:
3 events
Mid
Developer
Python
days
Mega Streak
Top 1
Streamlit
Developer
India
Highest experience points: 0 points,
0 activities in the last year
Python
349.1
exp.
Jupyter Notebook
92.4
exp.
CSS
171.1
exp.
HTML
197.5
exp.
JavaScript
130.1
exp.
SCSS
103.2
exp.
C++
52.3
exp.
JSON
99.1
exp.
Less
47.5
exp.
C
19.6
exp.
C#
21.4
exp.
List your work history, including any contracts or internships
Omdena
Apr 2023 - Jul 2023 (3 months)
Open Source Contributor
Omdena is the collaborative platform to build innovative, ethical, and efficient AI and Data Science solutions to real-world problems.
Add some compelling projects here to demonstrate your experience
AI Based Road Inspection System
Apr 2023 - Jun 2023
Omdena Mexico Chapter
This project employs machine learning to automate the identification of road defects, enhancing the efficiency of current inspections. A camera-based inspection system captures video streams of roads with and without abnormalities. The acquired data is analyzed using Matlab's machine learning toolbox for training and testing the network. Additionally, a user-friendly dashboard is developed to offer municipalities actionable recommendations for addressing road defects. The project comprises three key tasks: Data acquisition, Data Training/Testing, and Dashboard Building and Testing.
NLP with Disaster Tweets
May 2023 - Present
Omdena Giza Chapter
The analysis of social media data during natural disasters can be challenging due to the sheer volume of data generated and the need to quickly identify relevant information. Additionally, tweets are often short, informal, and contain non-standard language, making them difficult to analyze using traditional NLP techniques. As a result, there is a need for more advanced NLP techniques that can accurately classify disaster-related tweets and extract relevant information in real-time.
Water Quality Prediction System -Rwanda Chapter
May 2023 - Present
Omdena Rwanda Chapter
In this project, the primary goal is to develop an accurate and efficient machine learning model that can predict water quality based on a range of parameters such as Electrical conductivity of water, Amount of organic carbon in ppm, Amount of Trihalomethanes in μg/L, and turbidity. The model will be trained on a large dataset of historical water quality data and will be designed to provide predictions for water quality.
This section lets you add any degrees or diplomas you have earned.
Vellore Institute of Technology, Bhopal
Bachelor of Technology, Computer Science
Sep 2022 - Present