NIO/AI 2026 is afgelopen!

NIO/AI 2026 has concluded!

De NIO/AI 2026 is ten einde gekomen. Bedankt voor jullie deelname, en hopelijk tot volgend jaar!

The NIO/AI 2026 has concluded, thanks for your participation, and hope to see you next year!

Misschien zijn de onderstaande bronnen nuttig bij de voorbereiding op de wedstrijd van volgend jaar.

You may find the resources below useful for preparing to compete next year.

Bronnen

Resources

We raden aan om te beginnen met de conceptuele uitwerking en de implementatie.

We recommend starting with the intuition and implementation.

Begin hier

Start here

• Intro to Machine Learning in Kaggle Learn Intro to Machine Learning in Kaggle Learn
• Every Machine Learning Model Explained in 15 minutes Every Machine Learning Model Explained in 15 minutes
• A Gentle Introduction into Machine Learning door StatQuest A Gentle Introduction into Machine Learning by StatQuest
• But What is a neural network? door 3Blue1Brown But What is a neural network? by 3Blue1Brown

Machine Learning in Python

Machine Learning in Python

• Scikit-learn Tutorials Scikit-learn Tutorials
• PyTorch Tutorials PyTorch Tutorials

Als je meer wilt weten over de theorie achter de populairste methoden van machine learning en AI, zijn dit uitstekende startpunten.

If you would like to know more about the theory behind the most popular Machine Learning/AI methods, these are great starting points.

Verdiepende Wiskunde

Further Mathematics

• Essence of Calculus door 3Blue1Brown Essence of Calculus by 3Blue1Brown
• Essence of Linear Algebra door 3Blue1Brown Essence of Linear Algebra by 3Blue1Brown
• Probability Top 10 Must Knows Probability Top 10 Must Knows

Theorie van Machine Learning

Machine Learning Theory

• IAIO Training door Eljakim Schrijvers. IAIO Training by Eljakim Schrijvers. Begin bij hoofdstukken 1-6 Start from chapters 1-6
• Stanford Machine Learning Course Stanford Machine Learning Course