Lộ trình Học máy
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Hỏi AI về Lộ trình Học máy
Chú giải
Đề xuất
Lựa chọn thay thế
Tùy chọn
1 Mathematical Foundations
Linear Algebra
Scalars, Vectors, Tensors
Matrix Operations
Eigenvalues & Eigenvectors
Calculus
Derivatives & Chain Rule
Gradient, Jacobian, Hessian
Statistics & Probability
Basics of Probability
Bayes' Theorem
Types of Distribution
2 Programming Fundamentals
Python
Basic Syntax
Data Structures
OOP
Essential Libraries
Numpy
Pandas
Matplotlib & Seaborn
3 Data Preprocessing
Data Collection & Cleaning
Data Formats
Data Cleaning
Feature Engineering
Feature Scaling & Normalization
Dimensionality Reduction
4 Supervised Learning
Linear Regression
Logistic Regression
Support Vector Machines
Decision Trees & Random Forest
Gradient Boosting Machines
5 Unsupervised Learning
Clustering
K-Means
Hierarchical Clustering
DBSCAN
Dimensionality Reduction
PCA
Autoencoders
6 Deep Learning
Neural Network Basics
Perceptron, MLP
Backpropagation
Activation Functions
Deep Learning Libraries
TensorFlow
PyTorch
Keras
Deep Learning Architectures
CNNs
RNNs
Transformers
7 Model Evaluation
Evaluation Metrics
Classification Metrics
ROC-AUC
Confusion Matrix
Validation Techniques
K-Fold Cross Validation
LOOCV
8 Advanced Concepts
Natural Language Processing (NLP)
Text Preprocessing
Embeddings
Attention Models
Reinforcement Learning
Q-Learning
Deep-Q Networks