Top 10 ML Algorithms

Cute, colourful & beginner-friendly mini-course

✨ Tap a card → open full lesson page
📥 Works as a local / offline dashboard

🧠 Build your ML intuition, one cute card at a time

Use this dashboard as your home base. Each tile opens a dedicated page where the algorithm becomes a tiny adventure — with visuals, analogies, and friendly explanations.

Start with Linear Regression recommended first stop 🌈 View suggested learning path
Pick a card ➜ Read the story ➜ Try the ideas in code
📚 10 algorithms • 4 categories Perfect for quick revisits
🔍
🧩
📖 All lesson pages
Linear Regression📈 Logistic Regression🚪 Decision Trees🌳 Random Forest🌲 Support Vector Machines🧱 K-Nearest Neighbours👯‍♀️ K-Means Clustering🍬 Principal Component Analysis🔍 Naive Bayes💌 Neural Networks⚡

Pick your next algorithm 💡

Each card links to a full page with deeper explanations & fun visuals.

📈
Linear Regression
Supervised
The gentle slope-fitting friend: predict numbers with straight lines and simple maths.
⭐Start here
🚪
Logistic Regression
Supervised
Turns scores into probabilities so you can say “yes/no” with confidence (and a cute S-curve).
🎯Great for binary decisions
🌳
Decision Trees
Supervised
Follow the branches of “if… then…” questions until you reach a cute little leaf decision.
🌿Very human-readable
🌲
Random Forest
Supervised
A whole forest of trees that vote together. One tree might wobble, but the forest is steady.
🧺Ensemble magic
🧱
Support Vector Machines
Supervised
Builds the crispest wall between classes it can — then balances on the support vectors.
🧠Loves high-dimensional data
👯‍♀️
K-Nearest Neighbours
Supervised
“Show me your neighbours and I’ll guess who you are.” Super intuitive, surprisingly strong.
🧭Great intuition builder
🍬
K-Means Clustering
Unsupervised
Drop sweets on a table; watch them gather into colour-coded piles around their favourite centroid.
🌈Finds natural groups
🔍
PCA
Dim. Reduction
Spins the data cloud to find the most “interesting” directions, then flattens smartly.
🪄Less dimensions, same story
💌
Naive Bayes
Supervised
A sweet little probabilistic model that assumes independence and still works shockingly well.
⚡Lightning-fast for text
⚡
Neural Networks
Deep Learning
Many tiny “neurons” stacked into layers that slowly sculpt elegant decision boundaries.
🚀Foundation of modern AI

🌟 Cute learning path suggestion

Follow this colourful route if you want a gentle progression:

1. Linear Regression → 2. Logistic Regression → 3. Decision Trees → 4. Random Forest → 5. KNN → 6. K-Means → 7. Naive Bayes → 8. PCA → 9. SVM → 10. Neural Networks