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 +Jupyter/notebook +Gradient descent +Boosting (machine learning) +scikit-learn +IPython +Ron Meir +tfidf -Neural network"

Positive matches

• 0.230 + - Machine learning
• 0.107 + - Class imbalance
• 0.071 + - tf-idf
• 0.042 + - IPython notebook
• 0.033 + - Python/Modules
• 0.032 + - Python
• 0.023 + - Decision tree
• 0.023 + - Poker
• 0.021 + - Ulrike von Luxburg
• 0.021 + - Data clustering
• 0.020 + - Neuron
• 0.017 + - Recommender system
• 0.016 + - Yoav Freund
• 0.016 + - Rob Schapire
• 0.014 + - SSH tunneling
• 0.014 + - Artemy Kolchinsky
• 0.013 + - Random forest
• 0.013 + - Jupyter
• 0.011 + - skorch
• 0.011 + - Learning

Negative matches

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