My Journey into AI
Hey there! I’m Roshan Acharya, a curious learner and tech enthusiast passionate about Artificial Intelligence, Machine Learning, and Deep Learning. I love exploring how data can be transformed into insights, intelligence, and impact.
I write about my learning journey from breaking down complex ML concepts to sharing hands-on projects, experiments, and tutorials.
Hi, I’m Roshan Acharya, a Computer Engineering student from Nepal working on NLP and LLM-related projects and learning AI. I started this journey of learning AI exactly 1 year ago, a decision that changed how I learn, think and build.
Like many students, I was curious about AI. Terms like machine learning, deep learning, NLP and LLMs sounded exciting but I have no idea how it will go. I didn’t have a perfect roadmap or expert guidance.
How It All Started
My journey began with a subject called Foundations of Data Science, which was part of my academic curriculum. Through this course, I was introduced to basic Python, statistics, and classical machine learning concepts, along with essential practices like data cleaning and exploratory data analysis (EDA).
Instead of rushing to apply models, I focused on understanding why a model works, not just how to use it. This approach helped me build a strong conceptual foundation and develop a problem-solving mindset.
111Days of Challenge:
As I strengthened my basics, I participated 111Days of Challenge organized by Code for Change. This was the turning point where the habit of learning consistently was developed. I learned basic ML and DL concepts along with some hands on project like Car Price Prediction, Laptop Price Prediction, Image Compressor. These projects helped bridge the gap between theory and practice.
Learning the Imoirtance of Data
One major realization during this phase was that data collection is one of the most important steps in any ML or AI project. I started exploring web scraping, collecting real-world data, cleaning it, and transforming it into something meaningful.
Working with messy, real data gave me confidence and prepared me to take the next step.
Deep Learning and NLP
As I progressed in Machine Learning and Deep Learning, I became increasingly interested in how machines understand language, not just numbers and images. This curiosity led me to Natural Language Processing (NLP). Along the way, I explored transformer based model. I am currently working on finetuning projects and RAG system.
Still Learning, Still Training
I see this journey not as a destination.
I see it as a continuous learning process of learning, experimenting, and improving.
As long as the loss keeps decreasing and the learning never stops, I know the model is on the right path.
Training in progress. 🚀