Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem +Machine learning -Andrew Ng +Carlos Guestrin -Probability, Paradox, and the Reasonable Person Principle +Weka +Probability +Training dataset +Deep learning +Poker +Gradient descent -Neural network"

Positive matches

• 0.094 + - Class imbalance
• 0.022 + - Probability theory
• 0.022 + - Probability distribution
• 0.022 + - Neuron
• 0.014 + - Language
• 0.013 + - IPython notebook
• 0.012 + - Jupyter/notebook
• 0.012 + - Learning
• 0.011 + - Residual leanrning
• 0.009 + - Boosting (machine learning)
• 0.009 + - Recommender system
• 0.007 + - Artificial neural network
• 0.006 + - Reinforcement learning
• 0.006 + - Privacy and Deanonymization
• 0.006 + - GraphLab
• 0.006 + - Tom M. MItchell
• 0.006 + - Decision tree
• 0.006 + - Cluster analysis
• 0.006 + - Regular expression
• 0.006 + - Sargur Srihari

Negative matches

• 0.023 + - Paper/Srivastava2014
• 0.008 + - Ilya Sutskever
• 0.007 + - Jack Terwilliger
• 0.007 + - Neural Turing machine
• 0.007 + - Liquid state machine
• 0.005 + - word2vec
• 0.005 + - Recurrent neural network
• 0.004 + - Graph embedding
• 0.003 + - Dropout
• 0.003 + - Gensim
• 0.003 + - Hierarchical softmax
• 0.003 + - Tomas Mikolov
• 0.002 + - Skip-gram
• 0.002 + - sense2vec
• 0.001 + - Wolfgang Maass
• 0.001 + - Google
• 0.001 + - wiki2vec
• 0.001 + - Paper/Levy2014
• 0.001 + - Continuous embedding
• 0.001 + - Paper/Cooijmans2016