This repository is a clone of a Gitlab repo. This repo contains all of the code that i worked on during my semester of Applied Artificial Intelligence at AUAS.
The readme is split up into bootcamp and logbook. Bootcamp was a 2 week crash course of the basics of AI. Logbook contains assignments mapped to their respective topics. To navigate click the links.
| Dag | |
|---|---|
| 1 | Link |
| 2 | Link |
| 3 | Link |
| 4 | Link |
| 6 | Link |
| 7 | Link |
| 8 | Link |
| 9 | Link |
| Reflectie | Link |
| Probleemanalyse en basiskennis | Vereiste soort | Soort | Link naar bewijs | Sprint |
|---|---|---|---|---|
| Matrixvermenigvuldigen | T | Wiskunde notebook | 1 | |
| Determinant | T | Wiskunde notebook | 1 | |
| Partieel differentieren | T | Wiskunde notebook | 1 | |
| Activatiefuncties | T | Neural network from scratch | 1 | |
| Inverse matrix | T | Wiskunde notebook | 1 | |
| Transpose matrix | T | Neural network from scratch | 1 | |
| Inproduct | T | Wiskunde notebook | 1 | |
| Comprehensions | T | Basic python skills | 1 | |
| Dictionaries python | T | Basic python skills | 1 | |
| Slicing | T | Basic python skills | 1 | |
| Supervised vs unsupervised learning | K | Supervised vs Unsupervised | 1 | |
| Clustering | K | Clustering | 1 | |
| Stochastic gradient descent | T | Stochastic gradient descent | 2 | |
| Backpropagation | T | Neural network from scratch | 2 | |
| Geschikte performance measures kiezen | A | Citrus fruit | 1 | |
| Relatie wiskunde en AI | A | Relation math | 3 | |
| Inzicht verkrijgen in data | Vereiste soort | Soort | Link naar bewijs | |
| Scatter matrix | A | Citrus fruit | 1 | |
| Data visualiseren | A | Asteroids | 1 | |
| Normaalverdeling | T | Citrus fruit | 1 | |
| Regressie-analyse | T | Phishing | 1 | |
| Data voorbereiden en feature selection | ||||
| Z-scores | T | Bike rental | 1,2 | |
| Standaardafwijking | T | Citrus fruit | 1 | |
| Normaliseren | T | Asteroids | 1,2 | |
| T-toets | A | Citrus fruit | 1 | |
| ANOVA | T | Citrus fruit | 1,2 | |
| Correlatiematrix | A | Wine quality | 1 | |
| PCA | T | Bike rental | 2 | |
| Model selecteren, instellen, trainen en testen/valideren | ||||
| Geschikt algoritme kiezen | A | Citrus fruit | 3 | |
| KNN | A | Startup success prediction | 1 | |
| SVM | A | Phishing | 1 | |
| Naive Bayes | A | Asteroids | 1 | |
| Linear regression | A | Weather in Australia | 1 | |
| Logistic regression | A | Phishing | 1 | |
| Decision tree | A | ESRB ratings | 1 | |
| Random forest | A | Startup success prediction | 1 | |
| Dense neural network | A | ESRB ratings | 2 | |
| Convolutional neural network | A | Parasites | 2 | |
| Recurrent neural network | T | Recurrent NN | 2 | |
| Residual neural network | K | Residual | 2 | |
| Autoencoders | T | Autoencoders | 2 | |
| Adversarial learning | T | Adverserial | 3 | |
| Reinforcement learning | T | Reinforcement | 2 | |
| Model verbeteren | ||||
| Cross validation | T | Phishing | 1 | |
| Ensemble methods | T | Ensemble | 2 | |
| Transfer learning | T | Japanese text classification | 2 | |
| XAI extensies | A | Parasites | 3 | |
| Taalmodellen verfijnen en integreren | T | Japanese text classification | 3 | |
| Evalueren | ||||
| Overfitting en underfitting | A | ESRB ratings | 1 | |
| Learning curve | A | ESRB ratings | 1 | |
| Confusion matrix | A | Startup success prediction | 1 | |
| ROC curve | A | Citrus fruit | 1 | |
| Testen op bias en betrouwbaarheid | T | Placements | 3 | |
| Toepassingen | ||||
| Neural network from scratch | Neural network from scratch | 1 | ||
| Optimaliseren (gebruik GPU, Cloud, real-time) | T | Ik gebruik CUDA bij alle NN's die ik train | 3 | |
| Kwaliteit AAI software | T | AI quality | 3 |