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 +Jupyter/notebook +Andrew Ng +Artemy Kolchinsky +Poker +Machine learning -GraphLab"

Positive matches

• 0.097 + - Class imbalance
• 0.035 + - Deep learning
• 0.024 + - IPython notebook
• 0.021 + - Gradient descent
• 0.021 + - Brain network
• 0.019 + - Recommender system
• 0.014 + - IPython
• 0.013 + - SSH tunneling
• 0.013 + - Jupyter
• 0.012 + - Future of work
• 0.010 + - Boosting (machine learning)
• 0.009 + - Learning
• 0.007 + - Paradox
• 0.007 + - Privacy and Deanonymization
• 0.006 + - Aging brain
• 0.006 + - Regex
• 0.006 + - Random forest
• 0.005 + - scikit-learn
• 0.005 + - Spatial network
• 0.004 + - Network similarity

Negative matches

• 0.021 + - Network analysis libraries
• 0.004 + - Amazon Elastic Compute Cloud
• 0.003 + - Neural doodle
• 0.003 + - Language
• 0.003 + - Machine translation
• 0.003 + - Probability
• 0.003 + - Beer
• 0.002 + - Theano
• 0.002 + - Attention (Deep learning)
• 0.002 + - Attention
• 0.002 + - Residual leanrning
• 0.001 + - Meta learning
• 0.001 + - Residual Learning
• 0.001 + - Paper/Gatys2015
• 0.001 + - Generative adversarial network
• 0.001 + - Andy Connelly
• 0.000 + - Long short-term memory
• 0.000 + - Dropout
• 0.000 + - Deep generative models
• 0.000 + - Brain and deep learning