Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Computer science -Ulrike von Luxburg +Class imbalance +scikit-learn +tf-idf +Probability +Gradient descent -Gensim"

Positive matches

• 0.248 + - Machine learning
• 0.034 + - Neural network
• 0.031 + - Neuron
• 0.027 + - Decision tree
• 0.025 + - Text analysis
• 0.022 + - Data clustering
• 0.022 + - Probability theory
• 0.022 + - Probability distribution
• 0.021 + - Recommender system
• 0.016 + - Random forest
• 0.015 + - Pointwise mutual information
• 0.015 + - NLTK
• 0.014 + - Lexical feature selection
• 0.012 + - Jupyter/notebook
• 0.011 + - Deep learning
• 0.011 + - IPython notebook
• 0.011 + - Python/Modules
• 0.011 + - Poker
• 0.011 + - skorch
• 0.011 + - Tim Hopper

Negative matches

• 0.032 + - word2vec
• 0.004 + - Hierarchical softmax
• 0.003 + - Graph embedding
• 0.003 + - wiki2vec
• 0.001 + - sense2vec
• 0.001 + - Skip-gram
• 0.001 + - Network geometry
• 0.001 + - Softmax function
• 0.001 + - Clinical concept embedding
• 0.001 + - Paper/Levy2014
• 0.001 + - Paper/Levy2014a
• 0.001 + - William L. Hamilton
• 0.001 + - Paper/Hamilton2016
• 0.001 + - Google
• 0.001 + - Tomas Mikolov
• 0.001 + - TensorFlow
• 0.000 + - Residual Learning
• 0.000 + - Finkbeiner test
• 0.000 + - Deep generative models
• 0.000 + - Orthogonal Procrustes problem