Judul Buku : Machine Learning
BAB 1 Pengantar Machine Learning
BAB 2 Tipe Machine Learning (Supervised, Unsupervised, Reinforcement)
BAB 3 Preprocessing Data: Missing value, Normalisasi, Encoding
BAB 4 Representasi Data dan Feature Engineering
BAB 5 Linear Regression
BAB 6 Logistic Regression & Evaluasi Model (Confusion Matrix, Accuracy, AUC)
BAB 7 K-Nearest Neighbor (KNN)
BAB 8 Naive Bayes dan Decision Tree
BAB 9 Clustering dengan K-Means
BAB 10 Model Evaluation: Cross Validation, Overfitting, Underfitting
BAB 11 Ensemble Method (Random Forest, Bagging, Boosting)
BAB 12 Deep Learning Intro (Perbedaan ML vs DL, Peran Neural Network)
Ulasan
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