Ashish Lamsal
Hey there 👋
I'm Ashish Lamsal
Software Engineer (Python, React)
I am a Software Engineer currently handling backend development in Django for healthcare applications at Maitri Services. I specialize in Python, Django, FastAPI, React, and Next.js. I completed my Bachelor's Degree in Computer Engineering from the Institute of Engineering (IOE), Pulchowk Campus with a grade of 83.44%. My academic foundation includes data structures, algorithms, linux, deployment, and databases. I enjoy working on generative AI, large language models (LLM), and chatbots.
Let's connect! See my GitHub
My Recent Projects
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EaseAnnotate - Streamlining your annotation and extraction tasks

EaseAnnotate - Streamlining your annotation and extraction tasks

Eases the process of document annotation and information extraction, deploying advanced OCR technology to discern text from any scanned or digital document
Pythonify - Python Blog Site

Pythonify - Python Blog Site

Developed and currently maintaining a dynamic blog site using Next.js for the frontend, Tailwind CSS for styling, and Markdown for content creation.
Sentiment Analysis for Nepali Text

Sentiment Analysis for Nepali Text

Developed a web-based sentiment analysis application for Nepali text, classifying it into positive, negative, and neutral categories.
Latest from Blog
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Asynchronous Python [Part 1]: Mastering GIL, Multithreading, and Multiprocessing

Asynchronous Python [Part 1]: Mastering GIL, Multithreading, and Multiprocessing
9 min read

A comprehensive guide to understanding Asynchronous Python. Unveil the mysteries of Python's GIL, and master Python's concurrency mechanisms: multithreading and multiprocessing.
Python for Java Programmers

Python for Java Programmers
12 min read

A comprehensive guide to understanding Python for developers who are well-versed with Java.
Reinforcement Learning

Reinforcement Learning
6 min read

Reinforcement learning is a framework for solving control tasks (also called decision problems) by building agents that learn from the environment by interacting with it through trial and error and receiving rewards (positive or negative) as unique feedback.
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