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 -Data clustering +Gradient descent -Ulrike von Luxburg +Neuron +Image completion -Deep learning"

Positive matches

• 0.120 + - Class imbalance
• 0.102 + - Neural network
• 0.037 + - Generative adversarial network
• 0.032 + - Generative adversarial networks
• 0.028 + - Recommender system
• 0.013 + - Privacy and Deanonymization
• 0.013 + - Boosting (machine learning)
• 0.012 + - scikit-learn
• 0.012 + - Jupyter/notebook
• 0.011 + - Poker
• 0.011 + - IPython notebook
• 0.011 + - Learning
• 0.010 + - Future of work
• 0.009 + - Regular expression
• 0.007 + - Regex
• 0.007 + - Random forest
• 0.006 + - Decision tree
• 0.006 + - Sargur Srihari
• 0.006 + - Tom M. MItchell
• 0.006 + - Training dataset

Negative matches

• 0.020 + - Language
• 0.008 + - Reinforcement learning
• 0.005 + - Residual leanrning
• 0.004 + - Amazon EC2
• 0.003 + - Archetype
• 0.002 + - Q-learning
• 0.002 + - Cecilia Mascolo
• 0.002 + - Keras
• 0.002 + - Amazon Elastic Compute Cloud
• 0.002 + - Yann LeCun
• 0.002 + - Quoc Le
• 0.002 + - Thermostat
• 0.002 + - Paper/Gatys2015
• 0.002 + - Geoffrey Hinton
• 0.002 + - Autoencoder
• 0.002 + - Jürgen Schmidhuber
• 0.002 + - Convolutional neural network
• 0.002 + - TensorFlow
• 0.002 + - Andy Connelly
• 0.002 + - RNN