Hello! It's me
Hello! I'm Ashok Lamichhane, a tech-driven Machine Learning Engineer with expertise in website design using HTML/CSS and WordPress. I’m proficient in Python, MySQL, C, JavaScript, and the MERN Stack, contributing across the software development lifecycle — from analysis to testing and maintenance. I've worked with cross-functional and agile teams to deliver projects within time and budget constraints.
Passionate about AI, ML, Data Science and NLP, My Undergraduate Thesis focused on Nepali text Sentiment Analysis, Hate-Offence detection, Political Instance Detection and Multi-Label topic classification. I thrive on staying updated with industry trends to create scalable, efficient, and maintainable solutions, leveraging strong problem-solving and communication skills.
Download CV Hire MePython
MySQL
Html/CSS
Javascript
C
MERN Stack
BRAC University, Dhaka, Bangladesh
Pushpalal Memorial College, Kathmandu, Nepal
Develop Intelligent systems that leverage machine learning to analyze data, recognize patterns, and understand human language, enabling applications like chatbots, recommendation engines, and language translation tools.
Focus on creating visually appealing and user-friendly interfaces that provide an optimal browsing experience for your website visitors using HTML, CSS, JS & MERN JS.
Write and can teach clean, concise, and well-organized code that is easy to understand, maintain, and follow best practices.
Provides personalized guidance to deepen understanding, and Delivers structured lessons to cultivate critical thinking and foster a collaborative learning environment.
Provide excellent support by offering prompt and helpful assistance to address user inquiries and resolve issues effectively.
EDOS Classification using DL Models
This is the course project of Natural Language Processing (CSE440 - NLP II) from BRAC University in which I solved the classification problem of Explanatory Detection
of Online Sexism (EDOS). In this NLP project we did two tasks Task A and Task B. Task A solves the binary online sexism that is Sexism or Not Sexism whereas
Task B solves 4 class classifications of EDOS i.e. Threats, Derogation, Animosity & Prejudiced Discussion.
Here we got Accuracy and F1-score 82% for Task A and For Task B accuracy is 55% whereas F1-score is 49%.
You can access training dataset here, the GloVe embedding file here and the project report here.
CKD Classification using ML Models
This is the Machine Learning Project in which I solved the classification problem of Chronic Kidney Disease Classification Using five classification models.
This is the course project of CSE427 Machine Learning Course of BRAC Univeristy, in which we used 5 ML classification models to predict weather a person
have CKD or not based on different types of features. We used this dataset for this project.
Here are used Models:
Rentease Nepal: Online Hotel Booking Website
It is a full functioning Room Renting Website/Application from which we can book any types of hotel room,
rent normal house/room/flat, resorts and other type of tourist places.
It's a MERN Stack based website in which MongoDB (Unstructured) database used for store data.
Download the zip file and install necessary npm depencies to run it.
In the project directory, you can run:
npm start
Runs the app in the development mode. Open http://localhost:3000 to view it in your browser.
Fighter Plane Game
I made this project using OpenGL in Python for the Computer Graphics Course.
This project includes the basics of open GL, Midpoint circle algorithm, Midpoint line drawing,
and two types of Transformation i.e. Rotation, Translation. You can take a hint from this project
as you need to build something like this. I made this game full functioning as it have score
s well as level feature with varying difficulty level and we can also set life for gamers.
For installing and viewing this project in python openGL you must install numpy and other basic openGL requirements.
Keywords Hints: q - Rotate Left, e - Rotate Right, a - Moving Leftward, d - Moving Rightward, Space - To Shoot
Stock Price Prediction
This is a Machine Learning Project in which we can predict the price of the stock of any company by giving a dataset. In this project, we implemented five different models and found the best one. We used Linear Regression, Support Vector Regression (SVR), Random Forest, Decision Tree & and KNN. Using this model we can predict that if we buy stock at opening price and sell it at closing price how much profit or loss we can get. The model is useful for Traders as well as investors.
ClassEasy Educational App
This is educational application that can be used by different types of institutions where teacher can give assignment, take exams and keep track of students. Using this app online learning or teaching platfrom can be modified more effectively than the pre-existing one.
Online Pizza Delivery System
This is a fully functioning website from where we can order our desired pizza. I made this fully functionoing website using HTML, CSS, JavaScript, PHP and MySQL. I implemented all the food delivery application requirements like track order, payments, delivery boys and many more. You guys can take idea from this project for your own and contact me if any help needed reagarding this.