A wiki page of ML/ DL topics with <10 minutes of reading time. Intended as a quick reference to get a high level overview of the subject matter with details pertaining to its application.

• Linear regression
• Logistic regression
• Gradient descent
• SGD
• Momentum
• rmsprop
• Adam
• Decision tree
• Random forest
• Ensemble methods
  • Bagging
  • Boosting
    • Adaboost
    • XGBoost
  • Stacking
• SVM
• Kernel functions

• Deep neural network
• Activation functions
• Regression loss functions
• Classification loss functions
• Convolutional neural network
• Convolution layer
• Batch norm layer
• Pooling layers
• Layer normalization
• Recurrent neural network
• Long short term memory
• Transformer

• Word vectorization
• TF-IDF
• Word2vec
• Glove
• Stemming
• Lemmatization
• Tokenization
• POS tagging
• Doc2vec
• Topic modelling
• Synsets
• Ngrams/ Skipgrams

• PCA
• SVD
• t-sne

• GAN
• Autoencoders
• Variational autoencoders
• Gated recurrent unit
• Style transfer

• Alexnet
• VGG net
• Resnet
• Inception net
• Xception
• Spatial pyramid pooling

• Faster RCNN
• Loss functions for object detection
• Single shot detector
• YOLO
• Centernet

Contributions are welcome. Please go through the contribution guidelines.