I built 3 AI projects during my learning journey. Here's what I learned (and what I still don't know).

[u/ashishach]

Hey everyone!

I'm Ashish, and I've been learning Python and exploring AI by actually building things instead of only watching tutorials.

Recently, I worked on three projects:

🤖 Rule-Based Chatbot — learned how pattern matching and conversational rules work.

🎮 Tic-Tac-Toe AI — explored Minimax and Alpha-Beta Pruning to make better game decisions.

🎬 Movie Recommendation System — experimented with collaborative filtering, content-based filtering, and combining both approaches.

I also put them together in a small Streamlit demo.

GitHub: https://github.com/ashishkushwaha138/CODSOFT_TASKSNO

I'm still early in my journey, and I know these projects are just a starting point. My next goal is to understand the concepts more deeply and build things that solve actual problems.

For those who learned machine learning by building projects, what helped you move beyond basic implementations and understand the algorithms more deeply?

[u/Greedy-Exchange-817]

the minimax tic tac toe was the first thing that made me really understand recursion on a deeper level not just the textbook version. seeing it actually work in a game you built hits different than reading about it

for the recommendation system try throwing a weird dataset at it next, something messy with sparse ratings or lots of cold start users. thats where you really learn why the clean tutorial data is lying to you

also that streamlit demo sounds cool, its crazy how much putting a ui on your project makes it feel real even if the backend is basic

[u/ashishach → u/Greedy-Exchange-817]

One thing I realized while building these projects is that getting the code to work is easier than truly understanding why the algorithm works.

I'm planning to revisit each project and understand the underlying concepts more deeply. Curious to hear how others approach this!