Feature Engineering for Machine Learning

Index

Symbols

• ℓ² normalization, ℓ2 Normalization, Scaling Bag-of-Words with Tf-Idf Transformation, Scaling Bag-of-Words with Tf-Idf Transformation, Whitening and ZCA, k-Means Clustering
  • cross validation classifier accuracy, Tuning Logistic Regression with Regularization

A

• academic paper recommender (see recommender for academic papers)
• activation functions, Rectified Linear Unit (ReLU) Transformation
• AlexNet, Learning Image Features with Deep Neural Networks
  • convolutional layers, Convolutional Layers
  • fully connected layers, Fully Connected Layers
  • pooling layers, Pooling Layers
  • ReLU transformation, Rectified Linear Unit (ReLU) Transformation
  • response normalization layers, Response Normalization Layers
  • structure of, Structure of AlexNet-Structure of AlexNet
• anomaly detection of time series, use of PCA, Use Cases
• approximately leakage-proof statistics, Guarding against data leakage
• ASCII, Parsing and Tokenization
• audio data, Automating the Featurizer: Image Feature Extraction and Deep Learning

B

• back-off bin, What about rare categories?
• bag-of-n-grams, Bag-of-n-Grams
• bag-of-words (BoW) featurization, Bag-of-Words
  • scaling with tf-idf transformation, Scaling Bag-of-Words with Tf-Idf Transformation
• basis vectors, From Vectors to Subspaces, From Vectors to Subspaces
• bias, Overview of Linear Classification
• “Big Learning Made Easy—With Counts!” blog post, Bin Counting
• bigrams, Bag-of-n-Grams
• Bilenko, Misha, Bin Counting
• bin counting, Categorical Variables: Counting Eggs in the Age of Robotic Chickens, Bin Counting ...