> For the complete documentation index, see [llms.txt](https://can.gitbook.io/machine-learning-algorithm-summary/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://can.gitbook.io/machine-learning-algorithm-summary/master.md).

# Checklist

The topics that I plan to cover:

* Tree-based algorithms
  * Decision tree
  * CART
  * Adaboost
  * GBDT
  * Random Forest
  * XGBOOST
  * LightGBM
* SVM
* Clustering
  * Kmeans
  * GMM
* Anomaly Detection
* Linear regression
* Logistic regression
* Deep Learning Basic
  * DNN
  * RNN
  * LSTM
  * GRU
  * LSTM with Attention
  * Transformer
  * BERT
  * Word2Vec
* Object Detection
  * R-CNN
  * Fast R-CNN
  * Faster R-CNN
  * Mask Faster R-CNN
  * YOLO family (maybe)