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2026-yilda Machine Learning Engineer bo'lish uchun bosqichma-bosqich qo'llanma

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Dasturlash asoslari
Machine Learning
Dastlabki talablar
Python yo'l xaritasi
Tegishli yo'l xaritalari
  • AI Engineer yo'l xaritasi
  • MLOps yo'l xaritasi
  • AI va Data Scientist yo'l xaritasi
Kirish
ML engineer va AI engineer
Ko'nikmalar va mas'uliyatlar
ML Engineer kim?
Matematik asoslar
Linear Algebra
Calculus
Differentiation'dagi chain rule
Gradient, Jacobian va Hessian
Derivative'lar va partial derivative'lar
Scalar, vector va tensor'lar
Singular Value Decomposition
Matrix va matrix operation'lar
Eigenvalue'lar va diagonalization
Determinant'lar va inverse matrix
Statistics
Probability asoslari
Descriptive Statistics
Asosiy tushunchalar
Distribution turlari
Random variable'lar va PDF'lar
Bayes Theorem
Inferential Statistics
Grafiklar va diagrammalar
Probability
Discrete Mathematics
Python
Asosiy sintaksis
O'zgaruvchilar va ma'lumot tiplari
Conditionals
Ma'lumotlar tuzilmalari
Exceptions
Funksiyalar, built-in funksiyalar
Loops
Object Oriented Programming
Asosiy kutubxonalar
Numpy
Pandas
Matplotlib
Seaborn
Data Collection
Ma'lumot manbalari
Ma'lumotlar bazalari (SQL, No-SQL)
Internet
APIs
Mobile Apps
IoT
Ma'lumot formatlari
JSON
Parquet
CSV
Excel
Other Data Formats
Data Cleaning
Preprocessing Techniques
Data Cleaning
Dimensionality Reduction
Feature Engineering
Feature Selection
Feature scaling va normalization
Machine Learning
Machine learning turlari
Unsupervised Learning
Semi-supervised Learning
Supervised Learning
Reinforcement Learning
Self-supervised Learning
Machine Learning nima?
Supervised Learning nima?
Supervised Learning
Classification
Logistic Regression
Support Vector Machines
K-Nearest Neighbors (KNN)
Gradient Boosting Machines
Decision tree'lar va random forest
Regression
Linear Regression
Polynomial Regression
Unsupervised Learning
Unsupervised Learning nima?
Clustering
Dimensionality Reduction
Overlapping
Hierarchical
Exclusive
Probabilistic
Autoencoders
Principal Component Analysis
Reinforcement Learning
Reinforcement Learning nima?
Policy Gradient
Actor-Critic Methods
Deep-Q Networks
Q-Learning
Model Evaluation
Model Evaluation nima?
Baholash uchun metric'lar
Accuracy
Precision
Recall
F1-Score
ROC-AUC
Log Loss
Confusion Matrix
Deep Learning
Forward propagation
Back Propagation
Perceptron va multi-layer perceptron'lar
Activation Functions
Neural network (NN) asoslari
Loss Functions
Scikit-learn
Ridge
Lasso
Validation Techniques
LOOCV
K-Fold Cross Validation
Deep Learning Architectures
Convolutional Neural Network
Pooling
Padding
Convolution
Strides
CNN'larning qo'llanilishi
Image Classification
Image Segmentation
Image va video recognition
Recommendation Systems
Recurrent Neural Networks
RNN
GRU
LSTM
Attention Mechanisms
Autoencoders
Transformers
Multi-head Attention
Self-Attention
Generative Adversarial Networks
ML'dagi ilg'or tushunchalar
Natural Language Processing
Tokenization
Lemmatization
Stemming
Embeddings
Attention Models
Quyidagi tegishli yo'l xaritalarini ham ko'rib chiqing
AI va Data Scientist
MLOps
AI Engineer
AI Agents
Explainable AI
Train - Test Data
Ma'lumotlarni tayyorlash
Ma'lumotlarni yuklash
Tuning
Prediction
Model Selection
Deep Learning kutubxonalari
TensorFlow
Keras
PyTorch
Scikit-learn
ElasticNet Regularization
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