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) +IPython notebook +Class imbalance +Gradient descent +Jupyter/notebook -Neural network"

Positive matches

• 0.027 + - Recommender system
• 0.024 + - IPython
• 0.023 + - Text analysis
• 0.023 + - SSH tunneling
• 0.022 + - Ulrike von Luxburg
• 0.022 + - Data clustering
• 0.022 + - Neuron
• 0.022 + - scikit-learn
• 0.022 + - Poker
• 0.017 + - Pointwise mutual information
• 0.017 + - Ron Meir
• 0.016 + - Rob Schapire
• 0.016 + - Yoav Freund
• 0.015 + - Learning
• 0.014 + - Data science
• 0.014 + - Artemy Kolchinsky
• 0.013 + - Future of work
• 0.013 + - Jupyter
• 0.013 + - Lexical feature selection
• 0.013 + - tfidf

Negative matches

• 0.020 + - Paper/Srivastava2014
• 0.007 + - Ilya Sutskever
• 0.007 + - Jack Terwilliger
• 0.007 + - Neural Turing machine
• 0.006 + - Liquid state machine
• 0.006 + - Recurrent neural network
• 0.005 + - Dropout
• 0.005 + - word2vec
• 0.003 + - Hierarchical softmax
• 0.003 + - Graph embedding
• 0.002 + - wiki2vec
• 0.002 + - sense2vec
• 0.002 + - Skip-gram
• 0.001 + - Paper/Graves2014NTM
• 0.001 + - Paper/Hamilton2016
• 0.001 + - Google
• 0.001 + - Probability
• 0.001 + - WordRank
• 0.001 + - Tomas Mikolov
• 0.001 + - Paper/Levy2014