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Machine Learning (Applications (Natural language processing (Speech…
Machine Learning
Applications
Recommendation systems
Time series
Time series analysis
Time series forecasting
Computer vision
Objects detection
Image segmentation
Image classification
Analytics
Predictive analytics
Current state analytics
Optimization tasks
Natural language processing
Speech recognition
Text-to-speech
Natural language generation
Text analysis (tagging, parsing etc)
Machine translation
Summarization
Sentiment analysis
Entity recognition
Text classification
Keywords extraction
Topic modeling
Dimensionality reduction
Feature engineering for ML
Audio compression
Image compression
Anomaly detection
Outlier detection
Novelty detection
Fraud detection
Types of tasks
Supervised learning
Classification
Regression
Image segmentation
Unsupervised learning
Anomaly detection
Dimensionality reduction
Clustering
Reinforcement learning
Semi-supervised learning
Recommendation systems
Natural language generation
Image generation
Approaches
Single model
Traditional machine learning models
Naive Bayes models
K-nearest neighbors (KNN)
Decision tree
Logistic regression
Support vector machines (SVM)
k-Means
Polynomial regression
Linear regression
Statistical models
ARMA
ARIMA
Autoregressive
GARCH
Moving average
LDA
PCA
Factorization matrices
t-SNE
Neural networks
Deep neural networks
Recurrent Neural Networks (RNN)
Generative Adversarial Networks (GAN)
Convolutional Neural Networks (CNN)
Traditional (shallow) neural networks
Multi-model
Stacking
Bagging
Random Forest
Boosting
lightGBM
XGBoost