1. Modellen
1.1. Linear regression
1.2. Logistic regression
1.3. Decision Tree
1.4. Ensemble models
1.4.1. Random Forest
1.5. Deep learning
2. Artifacts
2.1. Data
2.2. Predictive model
2.3. Code
3. Evaluatie methoden
3.1. Classificatie
3.1.1. Confusion matrix
3.1.2. Area under the rock curve
3.1.3. Recall/ TPR
3.1.4. TNR
3.1.5. Accuracy
3.2. Regressie
3.2.1. Root mean square error (RMSE)
3.2.2. Mean square error (MSE)
3.2.3. Mean absolute percentage error (MAPE)
4. Overfitting
4.1. Oorzaken
4.1.1. Teveel iteraties
4.1.2. Te flexibele hypothese
4.1.3. Te weinig data samples
4.1.4. Teveel features
4.2. Remedies
4.2.1. Feature selection
4.2.2. Meer data samples
4.2.3. Minder iteraties
4.2.4. Simpeler hypothese
4.2.5. Regularisatie
4.2.6. Hyperparameter tuning
5. Data
5.1. Categorical
5.1.1. One-hot encoding
5.2. Numerical
6. Explainability
6.1. Feature importance
6.2. Feature attribution
7. Categorie
7.1. Supervised
7.2. Unsupervised
7.3. Reinforcement learning
8. Stappen in ML
8.1. Data verzamelen
8.2. Exploratory data analysis
8.2.1. Begrip opbouwen
8.2.1.1. Business understanding
8.2.1.2. Visualisaties
8.2.2. Verificatie
8.2.2.1. Missende data
8.2.2.2. Outliers
8.2.2.3. Schoonmaken van de data
8.2.3. Correlatie zoeken
8.3. Hypothese kiezen
8.4. Parameter learning (theta)
8.4.1. Kiezen cost function
8.4.1.1. Root mean square error (RMSE)
8.4.1.2. Mean square error (MSE)
8.4.1.3. Mean absolute percentage error (MAPE)
8.4.2. Gradient descent
8.4.2.1. Stochastic
8.4.2.2. Batch
8.5. Evalueren
9. MLOps
9.1. Volledige lifecycle van het product
9.1.1. Collect
9.1.2. Curate
9.1.3. Transform
9.1.4. Validate
9.1.5. Explore
9.1.6. Train
9.1.6.1. Continuous training
9.1.7. Evaluate
9.1.8. Formulate
9.1.8.1. Business objective
9.1.8.2. Cost of mistakes
9.1.8.3. Data availability
9.1.8.4. Evaluation metrics
9.1.8.5. ML - canvas
9.2. Extensie van DevOps
9.2.1. Continuous integration
9.2.1.1. Kwaliteit- en consistentietests
9.2.2. Continuous delivery
9.2.2.1. Snel itereren
9.2.2.2. Snel feedback
10. Hyperparameters
10.1. Batch size
10.2. Number of iterations
10.3. Lambda
10.4. Learning rate
11. Correlatie
11.1. Numeriek - numeriek
11.1.1. Scatterplot
11.2. Numeriek - categorisch
11.2.1. Bar chart
11.2.1.1. Confidence interval
11.3. Categorisch - categorisch
11.3.1. Grouped bar chart
11.3.2. Chi squared