Skip to content

Holberton ML Handbook (Albania)

Learn modern machine learning by doing. Clear steps, small wins, and projects that build real skills over 9 months.

Machine Learning

Start here

  • Begin with Tools, then move to Math, Data, Core ML, Deep Learning, and Generative AI.
  • Each page has a goal, steps, code, and links to go further.
  • Use the search bar to jump straight to what’s needed.

Who it’s for

  • Holberton School Albania trainees.
  • Motivated learners comfortable with basic Python, terminal, and Git.
  • Anyone who wants a focused ML guide without fluff.

What's inside

  • Tools: Set up Git/GitHub, Jupyter Notebooks, VS Code, and sharpen Python fundamentals
  • Math: Master linear algebra, NumPy, calculus, and probability/statistics for ML
  • Data: Collect, clean, visualize, and query data with pandas, SQL, and MongoDB
  • Core ML: Understand the ML lifecycle and implement supervised and unsupervised learning algorithms

Suggested path

  • Foundations first: Tools → Math → Data.
  • Core ML → Deep Learning → Capstone and deployment.
  • Practice steadily; reflect and iterate.

Study tips

  • Keep short notes after each lesson.
  • Recreate examples, then tweak them to test understanding.
  • Explain what was learned to a peer—teaching locks it in.

Word of encouragement

Keep going. Small steps, real projects, steady progress—skill by skill, week by week.

When it gets hard, return to the basics, build something small, and move forward again.

Robot Learning