Search "+Peter Norvig +Automated machine learning +Class imbalance problem +Travelling salesman problem -Probability, Paradox, and the Reasonable Person Principle +Cross validation +Cluster analysis +Artificial neural network +Data clustering +Ulrike von Luxburg +Recommender system -Netflix prize +scikit-learn +tfidf -Deep learning"

Positive matches

• 0.232 + - Machine learning
• 0.121 + - Class imbalance
• 0.077 + - tf-idf
• 0.025 + - Gradient descent
• 0.022 + - Decision tree
• 0.021 + - Brain network
• 0.014 + - Random forest
• 0.012 + - Learning
• 0.012 + - Boosting (machine learning)
• 0.012 + - skorch
• 0.011 + - Python/Modules
• 0.011 + - Poker
• 0.011 + - Jupyter/notebook
• 0.011 + - Future of work
• 0.011 + - IPython notebook
• 0.010 + - Tim Hopper
• 0.010 + - Python
• 0.009 + - Privacy and Deanonymization
• 0.008 + - Lexical feature selection
• 0.007 + - Spatial network

Negative matches

• 0.017 + - Language
• 0.008 + - Residual leanrning
• 0.008 + - Reinforcement learning
• 0.003 + - Q-learning
• 0.003 + - Amazon EC2
• 0.003 + - Andy Connelly
• 0.003 + - Archetype
• 0.002 + - Attention
• 0.002 + - Modeling animal behaviors with reinforcement learning
• 0.002 + - Machine translation
• 0.002 + - Geoffrey Hinton
• 0.002 + - Beer
• 0.002 + - Amazon Elastic Compute Cloud
• 0.002 + - Yoshua Bengio
• 0.002 + - Generative adversarial networks
• 0.002 + - Long short-term memory
• 0.002 + - word2vec
• 0.002 + - Theano
• 0.002 + - Thermostat
• 0.002 + - Paper/Gatys2015