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 +tf-idf +Boosting (machine learning) +Learning -Data clustering +Random forest +How to study -Gradient descent"

Positive matches

• 0.123 + - Class imbalance
• 0.037 + - scikit-learn
• 0.025 + - Recommender system
• 0.024 + - Text analysis
• 0.022 + - Ulrike von Luxburg
• 0.022 + - Deep learning
• 0.022 + - Decision tree
• 0.019 + - Pointwise mutual information
• 0.018 + - Programming interview
• 0.017 + - Yoav Freund
• 0.017 + - Ron Meir
• 0.017 + - Rob Schapire
• 0.017 + - tfidf
• 0.016 + - Gilles Louppe
• 0.016 + - Lexical feature selection
• 0.016 + - Michael Ramscar
• 0.014 + - Regular expression
• 0.013 + - Future of work
• 0.013 + - NLTK
• 0.013 + - Gensim

Negative matches

• 0.030 + - Neural network
• 0.026 + - Neuron
• 0.004 + - Ilya Sutskever
• 0.003 + - Probability
• 0.001 + - Neural Turing machine
• 0.001 + - Jack Terwilliger
• 0.001 + - Liquid state machine
• 0.001 + - Recurrent neural network
• 0.001 + - Paper/Graves2014NTM
• 0.001 + - Paper/Srivastava2014
• 0.001 + - Wolfgang Maass
• 0.001 + - Tomas Mikolov
• 0.001 + - Leland McInnes
• 0.000 + - Paper/Levy2014a