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Types of ML algorithms, Considerations for selecting a model, Use cases…
Types of ML algorithms
classical
models for text classification
naive bayes
logistic regression
recurrent neural networks
transformer-based models
BERT
GPT
Their variants
models for classic abnormality detection
k-nearest neighbors
Isolation forest
clustering
neural networks
neural networks
Recurrent neural networks (RNNs)
Long short-term memory (LSTM)
Feedforward neural networks
Convolutional neural networks (CNNs)
Considerations for selecting a model
data availability
explainability
performance metrics
problem type
Use cases for different algorithms
collaborative filtering
tree-based algorithms
matrix factorization
Techniques for combining models
ensembles
pretrained embeddings
feature extraction
Keeping up with new ML techniques and models
monitoring trends at major ML conferences
following researchers on Twitter