ML Concepts
Before building models you need the map of ML itself: what problems it solves and how to frame them.
Learn it
Learn supervised (labeled data → predict) vs unsupervised (find structure) learning; regression (predict a number) vs classification (predict a category); features vs target; training vs inference.
By the end you’ll be able to
- Distinguish supervised vs unsupervised
- Frame a problem as ML
Free resources
- Google — Supervised Learning intro (ML)(opens in a new tab)Start here
Clear on features, labels, how models learn
Free20 min - Kaggle Learn — Intro to Machine Learning(opens in a new tab)
Hands-on notebooks building a first model
Free3 hr - Kaggle — How Models Work (video)(opens in a new tab)
Gentle intro to the core idea of a model
Free8 min - Google — Machine Learning Crash Course(opens in a new tab)
Full free course covering regression vs classification
Freemulti-hour
Practice
For 5 real problems (spam filter, house price, customer segments…), label each as supervised/unsupervised and regression/classification.
Build it — your output
A one-pager framing a problem YOU care about as an ML task: what’s the target, what are the features, is it regression or classification.
Prove it — check yourself
You’re ready to move on when you can honestly say yes to each:
- Can you tell supervised from unsupervised?
- Can you spot regression vs classification?
- Can you identify features and target in a dataset?
Do it with AI
Use a free AI tool as your tutor and pair-programmer. Copy a prompt below into Claude, ChatGPT, or Gemini (for building, try Cursor or Copilot).
The habit: Try it yourself first — a little struggle is where the learning actually happens. Then ask for a hint before the answer — never copy blindly.
- Understand itClaude / ChatGPT / Gemini
I'm a beginner learning "ML Concepts". Explain it in simple terms with a real-world analogy, then ask me ONE question to check my understanding — don't reveal the answer.
- PracticeClaude / ChatGPT / Gemini
Give me 3 short practice problems on "ML Concepts" (my goal: distinguish supervised vs unsupervised), from easy to hard. Don't include the solutions yet — I'll try them first, then ask you to check.
- Get unstuckClaude / ChatGPT / Gemini
I'm stuck on this exercise about "ML Concepts": [paste your attempt here]. Give me ONE small hint to move forward — do NOT give me the full solution.
- Build & reviewCursor / Copilot
Here is my work for a "ML Concepts" task: [paste your code or answer]. Review it: point out what's wrong and WHY, and suggest improvements — but let me make the fixes myself.
- Prove itClaude / ChatGPT / Gemini
Quiz me on "ML Concepts". Ask me 5 questions one at a time, wait for my answer each time, then tell me if I'm right and briefly why.