Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Machine learning +Machine learning for healthcare -Data clustering +Gradient descent -Ulrike von Luxburg +Boosting (machine learning) +Poker -Neuron"

Positive matches

• 0.125 + - Class imbalance
• 0.027 + - Recommender system
• 0.018 + - Rob Schapire
• 0.018 + - Ron Meir
• 0.017 + - Yoav Freund
• 0.015 + - Privacy and Deanonymization
• 0.014 + - Learning
• 0.012 + - Jupyter/notebook
• 0.012 + - Future of work
• 0.011 + - scikit-learn
• 0.010 + - Regular expression
• 0.010 + - IPython notebook
• 0.008 + - Deep learning
• 0.007 + - Random forest
• 0.007 + - Decision tree
• 0.007 + - Artificial neural network
• 0.007 + - Tom M. MItchell
• 0.007 + - Image completion
• 0.007 + - Regex
• 0.007 + - Training dataset

Negative matches

• 0.032 + - Neural network
• 0.002 + - Neural Turing machine
• 0.002 + - word2vec
• 0.001 + - Gender bias
• 0.001 + - Paper/Levy2014a
• 0.001 + - GloVe
• 0.001 + - Clinical concept embedding
• 0.001 + - Long short-term memory
• 0.001 + - Paper/Graves2014NTM
• 0.001 + - Paper/Perozzi2014
• 0.001 + - Google
• 0.001 + - Chris McCormick
• 0.000 + - Paper/Hochreiter1997
• 0.000 + - Paper/Bahdanau2015
• 0.000 + - Rami Al-Rfou
• 0.000 + - Ivo Danihelka
• 0.000 + - KoNLPy
• 0.000 + - Sentiment analysis
• 0.000 + - Paper
• 0.000 + - Topic modeling